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BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
Sno. Topic Abstract Year 1. MATLAB2015_01 Machine Learning-Based
Coding Unit Depth
Decisions for Flexible
Complexity Allocation
in High Efficiency Video
Coding
In this paper, we propose a machine learning-based
fast coding unit (CU) depth decision method for High
EfficiencyVideo Coding (HEVC), which optimizes the
complexity allocationat CU level with given rate-
distortion (RD) cost constraints.First, we analyze quad-
tree CU depth decision process in HEVC
and model it as a three-level of hierarchical binary
decisionproblem. Second, a flexible CU depth decision
structureispresented, which allows the performances of
each CU depthdecision be smoothly transferred between
the coding complexityand RD performance. Then, a
three-output joint classifierconsists of multiple binary
classifiers with different parameters isdesigned to control
the risk of false prediction. Finally, a sophisticated RD-
complexity model is derived to determine the optimal
parameters for the joint classifier, which is capable of
minimizingthe complexity in each CU depth at given RD
degradationconstraints. Comparative experiments over
various sequencesshow that the proposed CU depth
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
decision algorithm canreduce the computational
complexity from 28.82% to 70.93%,and 51.45% on
average when compared with the original HEVCtest
model.
2. MATLAB2015_02 Distinguishing Local and
Global Edits for Their
Simultaneous Propagation
in a Uniform Framework
In propagating edits for image editing, some
editsareintended to affect limited local regions, while
others act
globally over the entire image. However, the ambiguity
problemin propagating edits is not adequately addressed
in existingmethods. Thus, tedious user inputrequirements
remain sincethe user must densely or repeatedly input
control samples tosuppress ambiguity. In this paper, we
address this challenge topropagate edits suitably by
marking edits for local or global
propagation and determining their reasonable propagation
scopesautomatically. Thus, our approach avoids
propagation conflicts,effectively resolving the ambiguity
problem. With the reduction ofambiguity, our method
allows fewer and less-precise control samples than
existing methods. Furthermore, we provide a uniform
framework to propagate local and global edits
simultaneously,helping the user to quickly obtain the
intended results withreduced labor. With our unified
framework, the potentiallyambiguous interaction between
local and global edits (evident
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
in existing methods that propagate these two edit types in
series)is resolved. We experimentally demonstrate the
effectiveness ofour method compared with existing
methods.
3. MATLAB2015_03 Face Recognition Across
Non-Uniform Motion
Blur, Illumination, and
Pose
Existing methods for performing face recognition
in the presence of blur are based on the convolution
model andcannot handle non-uniform blurring situations
that frequentlyarise from tilts and rotations in hand-held
cameras. In this paper,we propose a methodology for face
recognition in the presenceof space-varying motion blur
comprising of arbitrarily-shapedkernels. We model the
blurred face as a convex combination of
geometrically transformed instances of the focused
gallery face,and show that the set of all images obtained
by non-uniformlyblurring a given image forms a convex
set. We first propose a nonuniform blur-robust algorithm
by making use of the assumptionof a sparse camera
trajectory in the camera motion space tobuild an energy
function with l1-norm constraint on the camera
motion. The framework is then extended to handle
illuminationvariations by exploiting the fact that the set of
all images obtainedfrom a face image by non-uniform
blurring and changing theillumination forms a bi-convex
set. Finally, we propose an elegantextension to also
account for variations in pose.
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
4. MATLAB2015_04 Swarm Intelligence for
Detecting Interesting
Events
in Crowded Environments
This work focuses on detecting and localizing
anomalous events in videos of crowded scenes, i.e.
divergencesfrom a dominant pattern. Both motion and
appearance information are considered, so as to robustly
distinguish differentkinds of anomalies, for a wide range
of scenarios. A newlyintroduced concept based on swarm
theory, Histograms ofOriented Swarms (HOS), is applied
to capture the dynamicsof crowded environments. HOS,
together with the well knownHistograms of Oriented
Gradients (HOG), are combined tobuild a descriptor that
effectively characterizes each scene.These appearance
and motion features are only extracted within
spatiotemporal volumes of moving pixels to ensure
robustnessto local noise, increase accuracy in the
detection of local, nondominant anomalies, and achieve a
lower computational cost.Experiments on benchmark
datasets containing various situationswith human crowds,
as well as on traffic data, led to results that
surpassed the current state of the art, confirming the
method‘sefficacy and generality. Finally, the experiments
show that ourapproach achieves significantly higher
accuracy, especially forpixel-level event detection
compared to State of the Art (SoA)
methods, at a low computational cost.
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
5. MATLAB2015_05 Content-Based Image
Retrieval Using Features
Extracted From Halftoning-
Based Block
Truncation Coding
This paper presents a technique for Content-Based
Image Retrieval (CBIR) by exploiting the advantage of
lowcomplexity Ordered-Dither Block Truncation Coding
(ODBTC)for the generation of image content descriptor.
In encoding step,ODBTC compresses an image block into
correspondingquantizers and bitmap image. Two image
features are proposed toindex an image, namely Color
Co-occurrence Feature (CCF) andBit Pattern Features
(BPF), which are generated directly from
ODBTC encoded data streams without performing the
decodingprocess. The CCF and BPF of an image are
simply derived fromthe two ODBTC quantizers and
bitmap, respectively, by involvingthe visual codebook.
Experimental results show that the proposedmethod is
superior to the Block Truncation Coding (BTC) image
retrieval systems and the other former methods, and thus
provethat the ODBTC scheme is not only suited for
image compressionsince of its simplicity, but also offers a
simple and effectivedescriptor to index images in CBIR
2015
6. MATLAB2015_06 Approximation and
Compression with Sparse
Orthonormal Transforms
We propose a new transform design method that
targets the generation of compression-optimized
transforms fornext-generation multimedia applications.
The fundamental ideabehind transform compression is to
exploit regularity withinsignals such that redundancy is
minimized subject to a fidelitycost. Multimedia signals, in
particular images and video, are wellknown to contain a
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
diverse set of localized structures, leading tomany
different types of regularity and to nonstationary signal
statistics. The proposed method designs sparse
orthonormaltransforms (SOT) that automatically exploit
regularity over different signal structures and provides an
adaptation method thatdetermines the best representation
over localized regions. Unlikeearlier work that is
motivated by linear approximation constructsand model-
based designs that are limited to specific types of
signal regularity, our work uses general nonlinear
approximationideas and a data-driven setup to
significantly broaden its reach.We show that our SOT
designs provide a safe and principled
extension of the Karhunen-Loeve transform (KLT) by
reducingto the KLT on Gaussian processes and by
automatically exploitingnon-Gaussian statistics to
significantly improve over the KLT onmore general
processes. We provide an algebraic optimization
framework that generates optimized designs for any
desiredtransform structure (multi-resolution, block,
lapped, etc.) withsignificantly better n-term
approximation performance. For eachstructure, we
propose a new prototype codec and test over a
database of images. Simulation results show consistent
increasein compression and approximation performance
compared withconventional methods.
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
7. MATLAB2015_07 High-Resolution Face
Verification Using
Pore-Scale Facial Features
Face recognition methods, which usually represent
face images using holistic or local facial features, rely
heavily onalignment. Their performances also suffer a
severe degradationunder variations in expressions or
poses, especially when thereis one gallery per subject
only. With the easy access to highresolution (HR) face
images nowadays, some HR face databases
have recently been developed. However, few studies have
tackledthe use of HR information for face recognition or
verification.In this paper, we propose a pose-invariant
face-verificationmethod, which is robust to alignment
errors, using the HRinformation based on pore-scale
facial features. A new keypointdescriptor, namely, pore-
Principal Component Analysis (PCA)-Scale Invariant
Feature Transform (PPCASIFT)—adapted from
PCA-SIFT—is devised for the extraction of a compact set
ofdistinctive pore-scale facial features. Having matched
the porescale features of two-face regions, an effective
robust-fittingscheme is proposed for the face-verification
task. Experimentsshow that, with one frontal-view gallery
only per subject, ourproposed method outperforms a
number of standard verification
methods, and can achieve excellent accuracy even the
faces areunder large variations in expression and pose.
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
8. MATLAB2015_08 DERF: Distinctive
Efficient Robust Features
From
the Biological Modeling of
the P Ganglion Cells
Studies in neuroscience and biological vision have
shown that the human retina has strong computational
power,and its information representation supports vision
tasks on bothventral and dorsal pathways. In this paper, a
new local imagedescriptor, termed distinctive efficient
robust features (DERF), isderived by modeling the
response and distribution propertiesof the parvocellular-
projecting ganglion cells in the primate
retina. DERF features exponential scale distribution,
exponentialgrid structure, and circularly symmetric
function difference ofGaussian (DoG) used as a
convolution kernel, all of which areconsistent with the
characteristics of the ganglion cell arrayfound in
neurophysiology, anatomy, and biophysics. In addition,
a new explanation for local descriptor design is presented
fromthe perspective of wavelet tight frames. DoG is
naturally awavelet, and the structure of the grid points
array in ourdescriptor is closely related to the spatial
sampling of wavelets.The DoG wavelet itself forms a
frame, and when we modulate theparameters of our
descriptor to make the frame tighter, theperformance of
the DERF descriptor improves accordingly. This
is verified by designing a tight frame DoG, which leads to
much better performance. Extensive experiments
conducted inthe image matching task on the multiview
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
stereo correspondencedata set demonstrate that DERF
outperforms state of the artmethods for both hand-crafted
and learned descriptors, whileremaining robust and being
much faster to compute.
9. MATLAB2015_09 Blind Inpainting using ℓ0
and Total Variation
Regularization
In this paper, we address the problem of image
reconstruction with missing pixels or corrupted with
impulsenoise, when the locations of the corrupted pixels
are notknown. A logarithmic transformation is applied to
convert themultiplication between the image and binary
mask into anadditive problem. The image and mask terms
are then estimatediteratively with total variation
regularization applied on theimage, and ℓ0 regularization
on the mask term which imposessparseness on the support
set of the missing pixels. The resulting
alternating minimization scheme simultaneously
estimates theimage and mask, in the same iterative
process. The logarithmictransformation also allows the
method to be extended to theRayleigh multiplicative and
Poisson observation models. Themethod can also be
extended to impulse noise removal by relaxing
the regularizer from the ℓ0 norm to the ℓ1 norm.
Experimentalresults show that the proposed method can
deal with a largerfraction of missing pixels than two
phase methods which firstestimate the mask and then
reconstruct the image.
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
10. MATLAB2015_10 A Source-Channel Coding
Approach to Digital
Image Protection and Self-
Recovery
Watermarking algorithms have been widely applied
to the field of image forensics recently. One of these very
forensicapplications is the protection of images against
tampering. Forthis purpose, we need to design a
watermarking algorithmfulfilling two purposes in case of
image tampering: 1) detectingthe tampered area of the
received image and 2) recovering the lostinformation in
the tampered zones. State-of-the-art techniques
accomplish these tasks using watermarks consisting
ofcheckbits and reference bits. Check bits are used for
tamperingdetection, whereas reference bits carry
information about thewhole image. The problem of
recovering the lost reference bitsstill stands. This paper is
aimed at showing that having thetampering location
known, image tampering can be modeled
and dealt with as an erasure error. Therefore, an
appropriatedesign of channel code can protect the
reference bits againsttampering. In the present proposed
method, the total watermarkbit-budget is dedicated to
three groups: 1) source encoderoutput bits; 2) channel
code parity bits; and 3) check bits.In watermark
embedding phase, the original image is sourcecoded and
the output bit stream is protected using appropriate
channel encoder. For image recovery, erasure locations
detectedby check bits help channel erasure decoder to
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
retrieve theoriginal source encoded image. Experimental
results show thatour proposed scheme significantly
outperforms recent techniquesin terms of image quality
for both watermarked and recovered
image. The watermarked image quality gain is achieved
throughspending less bit-budget on watermark, while
image recoveryquality is considerably improved as a
consequence of consistentperformance of designed source
and channel codes.
11. MATLAB2015_11 Structured Sparse Priors for
Image Classification
Model-based compressive sensing (CS) exploits the
structure inherent in sparse signals for the design of better
signal recovery algorithms. This information about
structure isoften captured in the form of a prior on the
sparse coefficients,with the Laplacian being the most
common such choice (leadingto l1-norm minimization).
Recent work has exploited thediscriminative capability of
sparse representations for imageclassification by
employing class-specific dictionaries in theCS
framework. Our contribution is a logical extension of
theseideas into structured sparsity for classification. We
introducethe notion of discriminative class-specific priors
in conjunctionwith class specific dictionaries, specifically
the spike-and-slabprior widely applied in Bayesian sparse
regression. Significantly,the proposed framework takes
the burden off the demand forabundant training image
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
samples necessary for the successof sparsity-based
classification schemes. We demonstrate thispractical
benefit of our approach in important applications,
such as face recognition and object categorization.
12. MATLAB2015_12 Video Tracking Using
Learned Hierarchical
Features
In this paper, we propose an approach to learn
hierarchical features for visual object tracking. First, we
offlinelearn features robust to diverse motion patterns
from auxiliaryvideo sequences. The hierarchical features
are learned via a twolayer convolutional neural network.
Embedding the temporalslowness constraint in the
stacked architecture makes the learned
features robust to complicated motion transformations,
whichis important for visual object tracking. Then, given
a targetvideo sequence, we propose a domain adaptation
module toonline adapt the pre-learned features according
to the specifictarget object. The adaptation is conducted
in both layers ofthe deep feature learning module so as to
include appearanceinformation of the specific target
object. As a result, the learnedhierarchical features can be
robust to both complicated motiontransformations and
appearance changes of target objects. We
integrate our feature learning algorithm into three
tracking
methods. Experimental results demonstrate that
significant improvement can be achieved by using
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
ourlearned hierarchicalfeatures, especially on video
sequences with complicated motiontransformations.
13. MATLAB2015_13 A Global/Local Affinity
Graph for Image
Segmentation
Construction of a reliable graph capturing perceptual
grouping cues of an image is fundamental for
graph-cut based image segmentation methods. In this
paper, we propose a novel sparse global/local affinity
graph over superpixels of an input image to capture both
short and long range grouping cues, thereby
enabling perceptual grouping laws, e.g., proximity,
similarity, continuity, to enter in action through a
suitable graph cut algorithm. Moreover, we also evaluate
three major visual features, namely color, texture
and shape,for their effectiveness in perceptual
segmentation and propose a simple graph fusion scheme
to implement some recent findings from psychophysics
which suggest combining these visual features
with different emphases for perceptual grouping.
Specifically, an input image is first oversegmented into
superpixels at different scales. We postulate a gravitation
law based on empirical observations and divide
superpixels adaptively into small, medium and large sized
sets. Global grouping is achieved using medium
sized superpixels through a sparse representation of
superpixels‘ features by solving a `0-minimization
problem, thereby enabling continuity or propagation of
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
local smoothness over long range connections.
Small and large sized superpixels are then used to achieve
local smoothness through an adjacent graph
in a given feature space, thus implementing perceptual
laws, e.g., similarity and proximity. Finally, a
bipartite graph is also introduced to enable propagation of
grouping cues between superpixels of different
scales. Extensive experiments are carried out on the
Berkeley Segmentation Database in comparison with
several state of the art graph constructions.
14. MATLAB2015_14 A Database for Evaluating
No-Reference
Image Quality Assessment
Algorithms
This paper presents a new database, CID2013,
to address the issue of using no-reference (NR) image
qualityassessment algorithms on images with multiple
distortions.Current NR algorithms struggle to handle
images with manyconcurrent distortion types, such as real
photographic imagescaptured by different digital cameras.
The database consistsof six image sets; on average, 30
subjects have evaluated12–14 devices depicting eight
different scenes for a total of79 different cameras, 480
images, and 188 subjects (67% female).
The subjective evaluation method was a hybrid absolute
categoryrating-pair comparison developed for the study
and presentedin this paper. This method utilizes a
slideshow of all imageswithin a scene to allow the test
images to work as references toeach other. In addition to
mean opinion score value, the imagesare also rated using
2015
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
sharpness, graininess, lightness, and colorsaturation
scales. The CID2013 database contains images used
in the experiments with the full subjective data plus
extensivebackground information from the subjects. The
database is madefreely available for the research
community.
15. MATLAB2015_15 An Efficient MRF
Embedded Level Set
Method for
Image Segmentation
This paper presents a fast and robust level set
method for image segmentation. To enhance the
robustnessagainst noise, we embed a Markov random
field (MRF) energyfunction to the conventional level set
energy function. This MRFenergy function builds the
correlation of a pixel with its neighborsand encourages
them to fall into the same region. To obtain
a fast implementation of the MRF embedded level set
model,we explore algebraic multigrid (AMG) and sparse
fieldmethod(SFM) to increase the time step and decrease
thecomputationdomain, respectively. Both AMG and
SFM can be conducted ina parallel fashion, which
facilitates the processing of our methodfor big image
databases. By comparing the proposed fast and
robust level set method with the standard level set method
andits popular variants on noisy synthetic images,
synthetic apertureradar (SAR) images, medical images
and natural images, wecomprehensively demonstrate the
new method is robust againstvarious kinds of noises.
2015
BULK MATLAB IEEE TITLES 2015-16
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Especially, the new level set method cansegment an
image of size 500 by 500 within three seconds on
MATLAB R2010b installed in a computer with 3.30GHz
CPUand 4GB memory.
16. MATLAB2015_16 Weighted Guided Image
Filtering
It is known that local filtering-based edgepreserving
smoothing techniques suffer from halo artifacts.
In this paper, a weighted guided image filter (WGIF) is
introduced by incorporating an edge-aware weighting into
an existingguided image filter (GIF) to address the
problem. The WGIFinherits advantages of both global
and local smoothing filters inthe sense that: 1) the
complexity of the WGIF is O(N) for animage with N
pixels, which is same as the GIF and 2) the WGIF
can avoid halo artifacts like the existing global smoothing
filters.The WGIF is applied for single image detail
enhancement, singleimage haze removal, and fusion of
differently exposed images.Experimental results show
that the resultant algorithms produceimages with better
visual quality and at the same time haloartifacts can be
reduced/avoided from appearing in the finalimages with
negligible increment on running times.
2015
17. MATLAB2015_17 Distinctive Efficient
Robust Features From
the Biological Modeling of
Studies in neuroscience and biological vision have
shown that the human retina has strong computational
power,and its information representation supports vision
2015
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the P Ganglion Cells tasks on bothventral and dorsal pathways. In this paper, a
new local imagedescriptor, termed distinctive efficient
robust features (DERF), isderived by modeling the
response and distribution propertiesof the parvocellular-
projecting ganglion cells in the primateretina. DERF
features exponential scale distribution, exponentialgrid
structure, and circularly symmetric function difference of
Gaussian (DoG) used as a convolution kernel, all of
which areconsistent with the characteristics of the
ganglion cell arrayfound in neurophysiology, anatomy,
and biophysics. In addition,a new explanation for local
descriptor design is presented fromthe perspective of
wavelet tight frames. DoG is naturally a
wavelet, and the structure of the grid points array in our
descriptor is closely related to the spatial sampling of
wavelets.The DoG wavelet itself forms a frame, and when
we modulate theparameters of our descriptor to make the
frame tighter, theperformance of the DERF descriptor
improves accordingly. Thisis verified by designing a tight
frame DoG, which leads tomuch better performance.
Extensive experiments conducted inthe image matching
task on the multiview stereo correspondencedata set
demonstrate that DERF outperforms state of the
artmethods for both hand-crafted and learned descriptors,
whileremaining robust and being much faster to compute.
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18. MATLAB2015_18 Multi-task Pose-Invariant
Face Recognition
Face images captured in unconstrainedenvironments
usually contain significant pose
variation,whichdramatically degrades the performance of
algorithmsdesigned to recognize frontal faces. This paper
proposes a novelface identification framework capable of
handling the full rangeof pose variations within ±90° of
yaw. The proposed frameworkfirst transforms the original
pose-invariant face recognitionproblem into a partial
frontal face recognition problem. A robustpatch-based
facerepresentation scheme is then developed torepresent
the synthesized partial frontal faces. For each patch,
a transformation dictionary is learnt under the proposed
multitask learning scheme. The transformation dictionary
transformsthe features of different poses into a
discriminative subspace.Finally, face matching is
performed at patch level rather thanat the holistic level.
Extensive and systematic experimentationon FERET,
CMU-PIE, and Multi-PIE databases shows thatthe
proposed method consistently outperforms single-task-
basedbaselines as well as state-of-the-art methods for the
poseproblem. We further extend the proposed algorithm
for theunconstrained face verification problem and
achieve top-levelperformance on the challenging LFW
data set.
2015
19. MATLAB2015_19 A Feature-Enriched Existing blind image quality assessment (BIQA) 2015
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Completely Blind Image
Quality Evaluator
methods are mostly opinion-aware. They learn regression
modelsfrom training images with associated human
subjective scorestopredict the perceptual quality of test
images. Such opinion-awaremethods, however, require a
large amount of training sampleswith associated human
subjective scores and of a variety ofdistortion types. The
BIQA models learned by opinion-awaremethods often
have weak generalization capability, hereby limiting their
usability in practice. By comparison, opinion-
unawaremethods do not need human subjective scores for
training, andthus have greater potential for good
generalization capability.Unfortunately, thus far no
opinion-unaware BIQA method hasshown consistently
better quality prediction accuracy than theopinion-aware
methods. Here, we aim to develop an opinionunaware
BIQA method that can compete with, and
perhapsoutperform, the existing opinion-aware methods.
By integratingthe features of natural image statistics
derived from multiplecues, we learn a multivariate
Gaussian model of image patchesfrom a collection of
pristine natural images. Using the learnedmultivariate
Gaussian model, a Bhattacharyya-like distance isused to
measure the quality of each image patch, and thenan
overall quality score is obtained by average pooling.
Theproposed BIQA method does not need any distorted
sampleimages nor subjective quality scores for training,
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yet extensiveexperiments demonstrate its superior
quality-prediction performance to the state-of-the-art
opinion-aware BIQA methods.
20. MATLAB2015_20 Spatiotemporal Saliency
Detection for Video
Sequences Based on
Random Walk With Restart
A novel saliency detection algorithm for video
sequences based on the random walk with restart (RWR)
isproposed in this paper. We adopt RWR to detect
spatiallyand temporally salient regions. More specifically,
we first finda temporal saliency distribution using the
features of motiondistinctiveness, temporal consistency,
and abrupt change. Amongthem, the motion
distinctiveness is derived by comparing themotion
profiles of image patches. Then, we employ the temporal
saliency distribution as a restarting distribution of the
randomwalker. In addition, we design the transition
probability matrixfor the walker using the spatial features
of intensity, color, andcompactness. Finally, we estimate
the spatiotemporal saliencydistribution by finding the
steady-state distribution of the walker.
The proposed algorithm detects foreground salient objects
faithfully, while suppressing cluttered backgrounds
effectively,by incorporating the spatial transition matrix
and the temporalrestarting distribution systematically.
Experimental resultson various video sequences
demonstrate that the proposedalgorithm outperforms
conventional saliency detection algorithmsqualitatively
2015
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and quantitatively.
21. MATLAB2015_21 Sorted Consecutive Local
Binary Pattern
for Texture Classification
In this paper, we propose a sorted consecutive local
binary pattern (scLBP) for texture classification.
Conventionalmethods encode only patterns whose spatial
transitions are notmore than two, whereas scLBP encodes
patterns regardless oftheir spatial transition. Conventional
methods do not encode
patterns on account of rotation-invariant encoding; on the
otherhand, patterns with more than two spatial transitions
havediscriminative power. The proposed scLBP encodes
all patternswith any number of spatial transitions while
maintaining theirrotation-invariant nature by sorting the
consecutive patterns.In addition, we introduce dictionary
learning of scLBP basedon kd-tree which separates data
with a space partitioningstrategy. Since the elements of
sorted consecutive patterns liein different space, it can be
generated to a discriminative codewith kd-tree. Finally,
we present a framework in which scLBPs
and the kd-tree can be combined and utilized. The results
of experimental evaluation on five texture data sets—
Outex,CUReT, UIUC, UMD, and KTH-TIPS2-a—
indicate that ourproposed framework achieves the best
classification rate onthe CUReT, UMD, and KTH-TIPS2-
a data sets compared withconventional methods. The
results additionally indicate that onlya marginal
2015
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difference exists between the best classification rate
of conventional methods and that of the proposed
frameworkon the UIUC and Outex data sets.
22. MATLAB2015_22 Robust 2D Principal
Component Analysis:
A Structured Sparsity
Regularized Approach
Principal component analysis (PCA) is widely
used to extract features and reduce dimensionality in
variouscomputer vision and image/video processing tasks.
Conventionalapproaches either lack robustness to outliers
and corrupted dataor are designed for one-dimensional
signals. To address thisproblem, we propose a robust
PCA model for two-dimensional
images incorporating structured sparse priors, referred to
as structured sparse 2D-PCA. This robust model
considersthe prior of structured and grouped pixel values
in twodimensions. As the proposed formulation is jointly
nonconvexand nonsmooth, which is difficult to tackle by
joint optimization,we develop a two-stage alternating
minimization approachto solve the problem. This
approach iteratively learns theprojection matrices by
bidirectional decomposition and utilizesthe proximal
method to obtain the structured sparse outliers.
By considering the structured sparsity prior, the proposed
model becomes less sensitive to noisy data and outliers in
twodimensions. Moreover, the computational cost
indicates that therobust two-dimensional model is capable
of processing quartercommon intermediate format video
2015
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in real time, as well as
handling large-size images and videos, which is often
intractablewith other robust PCA approaches that involve
image-to-vectorconversion. Experimental results on
robust face reconstruction,video background subtraction
data set, and real-world videos
show the effectiveness of the proposed model compared
withconventional 2D-PCA and other robust PCA
algorithms.
23. MATLAB2015_23 Accurate Vessel
Segmentation With
Constrained B-Snake
We describean active contour framework with
accurate shape and size constraints on the vessel cross-
sectionalplanes to produce the vessel segmentation. It
startswith a multiscale vessel axis tracing in a 3D
computedtomography (CT) data, followed by vessel
boundary delineationon the cross-sectional planes derived
from the extracted axis.The vessel boundary surface is
deformed under constrainedmovements on the cross
sections and is voxelized to producethe final vascular
segmentation. The novelty of this paper lies
in the accurate contour point detection of thin vessels
basedon the CT scanning model, in the efficient
implementation ofmissing contour points in the
problematic regions and in theactive contour model with
accurate shape and size constraints.The main advantage
of our framework is that it avoidsdisconnected and
2015
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incomplete segmentation of the vessels in theproblematic
regions that contain touching vessels (vessels in close
proximity to each other), diseased portions (pathologic
structureattached to a vessel), and thin vessels. It is
particularly suitablefor accurate segmentation of thin and
low contrast vessels. Ourmethod is evaluated and
demonstrated on CT data sets fromour partner site, and its
results are compared with three related
methods. Our method is also tested on two publicly
availabledatabases and its results are compared with the
recentlypublished method. The applicability of the
proposed methodto some challenging clinical problems,
the segmentation of thevessels in the problematic regions,
is demonstrated with goodresults on both quantitative and
qualitative experimentations;our segmentation algorithm
can delineate vessel boundaries thathave level of
variability similar to those obtained manually.
24. MATLAB2015_24 PatchMatch With Potts
Model for Object
Segmentation and Stereo
Matching
This paper presents a unified variationalformulation for
joint object segmentation and stereo matching,which
takes both accuracy and efficiency into account. In
ourapproach, depth-map consists of compact objects, each
object isrepresented through three different aspects: 1) the
perimeter inimage space; 2) the slanted object depth
plane; and 3) the planarbias, which is to add an additional
level of detail on top of eachobject plane in order to
2015
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model depth variations within an object.Compared with
traditional high quality solving methods in lowlevel, we
use a convex formulation of the multilabel Potts Model
with PatchMatch stereo techniques to generate depth-map
ateach image in object level and show that accurate
multiple viewreconstruction can be achieved with our
formulation by meansof induced homography without
discretization or staircasingartifacts. Our model
isformulated as an energy minimizationthat is optimized
via a fast primal-dual algorithm, whichcan handle several
hundred object depth segments efficiently.Performance
evaluations in the Middlebury benchmark data sets
show that our method outperforms the traditional integer-
valueddisparity strategy as well as the original
PatchMatch algorithmand its variants in subpixel accurate
disparity estimation.The proposed algorithm is also
evaluated and shown to produceconsistently good results
for various real-world data sets(KITTI benchmarkdata
sets and multiview benchmark
data sets).
25. MATLAB2015_25 Robust Representation and
Recognition of
Facial Emotions Using
Extreme Sparse
Learning
Recognition of natural emotions from human faces is an
interesting topic with a wide range of potential
applications like human-computer interaction, automated
tutoring systems, image and video retrieval, smart
environments,and driver warning systems. Traditionally,
2015
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facial emotion recognition systems have been evaluated
on laboratorycontrolled data, which is not representative
of the environment faced in real-world applications. To
robustly recognizefacial emotions in real-world natural
situations, this paper proposes an approach calledExtreme
Sparse Learning(ESL), which has the ability to jointly
learn a dictionary (set of basis) and a non-linear
classification model. Theproposed approach combines the
discriminative power of Extreme Learning Machine
(ELM) with the reconstructionproperty of sparse
representation to enable accurate classification when
presented with noisy signals and imperfect data
recorded in natural settings. Additionally, this work
presents a new local spatio-temporal descriptor that is
distinctiveand pose-invariant. The proposed framework is
able to achieve state-of-the-art recognition accuracy on
both actedand spontaneous facial emotion databases.
26. MATLAB2015_26 Adaptive Image Denoising
by Targeted Databases
We propose a data-dependent denoising procedure
to restore noisy images. Different from existing denoising
algorithms which search for patches from either the noisy
imageor a generic database, the new algorithm finds
patches froma database that contains relevant patches. We
formulate thedenoising problem as an optimal filter
2015
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design problem and maketwo contributions. First, we
determine the basis function ofthe denoising filter by
solving a group sparsity minimizationproblem. The
optimization formulation generalizes existingdenoising
algorithms and offers systematic analysis of the
performance. Improvement methods are proposed
toenhance the patchsearch process. Second, we determine
the spectral coefficients ofthe denoising filter by
considering a localized Bayesian prior. The
localized prior leverages the similarity of the targeted
database,alleviates the intensive Bayesian computation,
and links the newmethod to the classical linear minimum
mean squared errorestimation. We demonstrate
applications of the proposed methodin a variety of
scenarios, including text images, multiview images,
and face images. Experimental results show the
superiority of thenew algorithm over existing methods.
27. MATLAB2015_27 Progressive Halftone
Watermarking Using
Multi-layer Table Lookup
Strategy
In this work, a halftoning-based multi-layer watermarking
of low computational complexity is proposed. An
additional data hiding technique is also employed to
embed multiple watermarks into the watermark to be
embedded to improve the security and embedding
capacity. At the encoder, the Efficient Direct Binary
Search (EDBS) method is employed to generate 256
reference tables to ensure the output is in halftone format.
2015
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Subsequently, watermarks are embedded by a set of
optimized compressed tables with various textural angles
for table lookup. At the decoder, the Least-MeanSquare
(LMS) metric is considered to increases the differences
among those generated phenotypes.
28. MATLAB2015_28 Learning Multiple Linear
Mappings for Efficient
Single Image Super-
Resolution
Example learning-based superresolution (SR)
algorithms show promise for restoring a high-resolution
(HR)image from a single low-resolution (LR) input. The
most popularapproaches, however, are either time- or
space-intensive, whichlimits their practical applications in
many resource-limitedsettings. In this paper, we propose
a novel computationallyefficient single image SR method
that learns multiple linear
mappings (MLM) to directly transform LR feature
subspacesinto HR subspaces. In particular, we first
partition the largenonlinear feature space of LR images
into a cluster of linearsubspaces. Multiple LR
subdictionaries are then learned, followedby inferring the
corresponding HR subdictionaries based on the
assumption that the LR–HR features share the same
representation coefficients. We establish MLM from the
input LR featuresto the desired HR outputs in order to
achieve fast yet stable SRrecovery. Furthermore, in
orderto suppress displeasing artifactsgenerated by the
MLM-based method, we apply a fast nonlocalmeans
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algorithm to construct a simple yet effective
similaritybased regularization term for SR enhancement.
Experimentalresults indicate that our approach is both
quantitatively andqualitatively superior to other
application-oriented SR methods,while maintaining
relatively low time and space complexity.
29. MATLAB2015_29 Cross-Domain Person Re-
Identification Using
Domain Adaptation
Ranking SVMs
This paper addresses a new person re-identification
problem without label information of persons under
nonoverlapping target cameras. Given the matched
(positive) andunmatched (negative) image pairs from
source domain cameras,as well as unmatched (negative)
and unlabeled image pairs fromtarget domain cameras,
we propose an Adaptive Ranking Support Vector
Machines (AdaRSVM) method for re-identificationunder
target domain cameras without person labels. To
overcome
the problems introduced due to the absence of matched
(positive)image pairs in the target domain, we relax the
discriminativeconstraint to a necessary condition only
relying on the positivemean in the target domain. To
estimate the target positivemean, we make use of all the
available data from source andtarget domains as well as
constraints in person re-identification.Inspired by
adaptive learning methods, a new discriminative
model with high confidence in target positive mean and
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lowconfidence in target negative image pairs is developed
by refiningthe distance model learnt from the source
domain. Experimentalresults show that the proposed
AdaRSVM outperforms existing supervised or
unsupervised, learning or non-learning reidentification
methods without using label information in target
cameras. Moreover, our method achieves better re-
identificationperformance than existing domain
adaptation methods derivedunder equal conditional
probability assumption.
30. MATLAB2015_30 Structure-Sensitive
Saliency Detection
via Multilevel Rank
Analysis in
Intrinsic Feature Space
This paper advocates a novel multiscale,
structure-sensitive saliency detection method, which can
distinguish multilevel, reliable saliency from various
naturalpictures in a robust and versatile way. One key
challengefor saliency detection is to guarantee the entire
salient objectbeing characterized differently from
nonsalient background.To tackle this, our strategy is to
design a structure-awaredescriptor based on the intrinsic
biharmonic distance metric.One benefit of introducing
this descriptor is its ability tosimultaneously integrate
local and global structure information,which is extremely
valuable for separating the salient objectfrom nonsalient
background in a multiscale sense. Upon devisingsuch
powerful shape descriptor, the remaining challenge is
to capture the saliency to make sure that salient subparts
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actually stand out among all possible candidates. Toward
thisgoal, we conduct multilevel low-rank and sparse
analysis inthe intrinsic feature space spanned by the shape
descriptorsdefined on over-segmented super-pixels. Since
the low-rankproperty emphasizes much more on stronger
similarities amongsuper-pixels, we naturally obtain a
scale space along the rank
dimension in this way. Multiscale saliency can be
obtained bysimply computing differences among the low-
rank componentsacross the rank scale. We conduct
extensive experiments onsome public benchmarks, and
make comprehensive, quantitativeevaluation between our
method and existing state-of-the-arttechniques. All the
results demonstrate the superiority of ourmethod in
accuracy, reliability, robustness, and versatility.
31. MATLAB2015_31 Depth Reconstruction From
Sparse Samples:
Representation, Algorithm,
and Sampling
The rapid development of 3D technology and
computer vision applications has motivated a thrust of
methodologies for depth acquisition and estimation.
However,existing hardware and software acquisition
methods havelimited performance due to poor depth
precision, low resolution,and high computational cost. In
this paper, we present acomputationally efficient method
to estimate dense depth mapsfrom sparse measurements.
There are three main contributions.First, we provide
empirical evidence that depth maps can beencoded much
2015
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more sparsely than natural images using common
dictionaries, such as wavelets and contourlets. We also
showthat a combined wavelet–contourlet dictionary
achieves betterperformance than using either dictionary
alone. Second, wepropose an alternating direction method
of multipliers (ADMM)for depth map reconstruction. A
multiscale warm start procedure
is proposed to speed up the convergence. Third, we
proposea two-stage randomized sampling scheme to
optimally choosethe sampling locations, thus maximizing
the reconstructionperformance for a given sampling
budget. Experimentalresults show that the proposed
method produces high-qualitydense depth estimates, and
is robust to noisy measurements.Applications to real data
in stereo matching are demonstrated.
32. MATLAB2015_32 Image Denoising by
Exploring External
and Internal Correlations
Single image denoising suffers from limited data
collection within a noisy image. In this paper, we propose
anovel image denoising scheme, which explores both
internaland external correlations with the help of web
images. Foreach noisy patch, we build internal and
external data cubesby finding similar patches from the
noisy and web images,respectively. We then propose
reducing noise by a two-stagestrategy using different
filtering approaches. In the first stage,since the noisy
patch may lead to inaccurate patch selection, we
2015
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propose a graph based optimization method to improve
patchmatching accuracy in external denoising. The
internal denoisingis frequency truncation on internal
cubes. By combining theinternal and external denoising
patches, we obtain a preliminarydenoising result. In the
second stage, we propose reducing noiseby filtering of
external and internal cubes, respectively, ontransform
domain. In this stage, the preliminary denoising result
not only enhances the patch matching accuracy but also
providesreliable estimates of filtering parameters. The
final denoisingimage is obtained by fusing the external
and internal filteringresults. Experimental results show
that our method constantlyoutperforms state-of-the-art
denoising schemes in both subjectiveand objective quality
measurements, e.g., it achieves >2 dB gain
compared with BM3D at a wide range of noise levels.
33. MATLAB2015_33 Motion-Compensated
Coding and Frame Rate
Up-Conversion: Models
and Analysis
Block-based motion estimation (ME) and motion
compensation (MC) techniques are widely used in
modernvideo processing algorithms and compression
systems. The greatvariety of video applications and
devices results in diversecompression specifications, such
as frame rates and bit rates.
In this paper, we study the effect of frame rate and
compressionbit rate on block-based ME and MC as
commonly utilized ininter-frame coding and frame rate
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up-conversion (FRUC). Thisjoint examination yields a
theoretical foundation for comparingMC procedures in
coding and FRUC. First, the video signal islocally
modeled as a noisy translational motion of an image.
Then, we theoretically model the motion-compensated
predictionof available and absent frames as in coding and
FRUCapplications, respectively. The theoretic MC-
prediction erroris studied further and its autocorrelation
function is calculated, yielding useful separable-
simplifications for the codingapplication. We argue that a
linear relation exists betweenthe variance of the MC-
prediction error and temporaldistance. While the relevant
distance in MC coding is betweenthe predicted and
reference frames, MC-FRUC is affected bythe distance
between the frames available for interpolation.We
compare our estimates with experimental results
andshowthat the theory explains qualitatively the
empirical behavior.Then, we use the models proposed to
analyze a system forimproving of video coding at low bit
rates, using a spatiotemporal scaling. Although this
concept is practically employed invarious forms, so far it
lacked a theoretical justification. We hereharness the
proposed MC models and present a
comprehensiveanalysis of the system, to qualitatively
predict the experimental
results.
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34. MATLAB2015_34 Fractal Analysis for
Reduced Reference
Image Quality Assessment
In this paper, multifractal analysis is adapted to
reduced-reference image quality assessment (RR-IQA). A
novelRR-QA approach is proposed, which measures the
differenceof spatial arrangement between the reference
image and thedistorted image in terms of spatial
regularity measured by fractaldimension. An image is
first expressed in Log-Gabor domain.Then, fractal
dimensions are computed on each Log-Gaborsubband and
concatenated as a feature vector. Finally, the
extracted features are pooled as the quality score of the
distortedimage using 1 distance. Compared with existing
approaches, theproposed method measures image quality
from the perspectiveof the spatial distribution of image
patterns. The proposedmethod was evaluated on seven
public benchmark data sets.Experimental results have
demonstrated the excellentperformance of the proposed
method in comparison withstate-of-the-art approaches.
2015
35. MATLAB2015_35 Criteria-Based Modulation
for Multilevel Inverters
Pulse-width modulation schemes are aimed at adjusting
the fundamental component while reducing the harmonic
content of an inverter output voltage or current. This
paperaddresses the topic of optimal inverter operation in
reference toa given objective function. The objective
function could embodyeither a single performance
criterion, such as voltage or currenttotal harmonic
2015
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distortion, or a weighted sum of multiple criteria.
The proposed method ensures primacy of the chosen
solutionwhile imposing no restriction over its modulation
index. Inparticular, operating the inverter by the chosen
solution wouldresult in performances superior to any
other modulation schemecommutating in an equal number
of switching angles per fundamental cycle. The proposed
method allows for the consideration
of practical inverter constraints and prevents the
possibility ofimpractical switching sequence. A detailed
investigation of themethod is given, accompanied by two
practical cases minimizing,respectively, phase-voltage
THD and line-current THD of a threelevel inverter.
Selected simulation and experimental results are
presented to validate the theoretical part.
36. MATLAB2015_36 A Fully Soft-Switched
Single Switch Isolated
DC-DC Converter
This paper proposes a soft-switched single switch
isolated converter. The proposed converter is able to offer
lowcost and high power density in step up application due
to thefollowing features: ZCS turn-on and ZVS turn-off
of switch andZCS turn-off of diodes regardless of voltage
and load variation;low rated lossless snubber; reduced
transformer volumecompared to flyback based converters
due to low magnetizingcurrent. Experimental results on a
100kHz, 250W prototype areprovided to validate the
proposed concept.
2015
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37. MATLAB2015_37 Functional Modeling of
Symmetrical Multipulse
Autotransformer Rectifier
Units
for Aerospace Applications
This paper aims to develop a functional model of
symmetrical multipulse autotransformer rectifier units
(ATRUs) formore-electric aircraft (MEA) applications.
The ATRU is seen asthe most reliable way readily to be
applied in the MEA. Interestingly, there is no model
ofATRUs suitable for unbalanced or faulty
conditions at the moment. This paper is aimed to fill this
gap anddevelop functional models suitable for both
balanced and unbalanced conditions. Using the fact that
the dc voltage and currentare strongly related to the
voltage and current vectors at the acterminals of ATRUs,
a functional model has been developed for theasymmetric
ATRUs. The developed functional models are
validatedthrough simulation and experiment. The
efficiency of the developedmodel is also demonstrated by
comparing with corresponding detailed switching models.
The developed functional model showssignificant
improvement of simulation efficiency, especially
underbalanced conditions.
2015
38. MATLAB2015_38 Model Predictive Control
Methods to Reduce
Common-Mode Voltage
for Three-Phase Voltage
Source Inverters
In this paper, we propose model predictive control
methods to reduce the common-mode voltage of three-
phase voltagesource inverters (VSIs). In the reduced
common-mode voltage-model predictive control (RCMV-
MPC) methods proposed in this paper,only nonzero
2015
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voltage vectors are utilized to reduce the common-mode
voltage as well as to control the load currents. In addition,
twononzero voltage vectors are selected from the cost
function at every sampling period, instead of using only
one optimal vector during onesampling period. The two
selected nonzero vectors are distributed in one sampling
period in such a way as to minimize the error between
the measured load current and the reference. Without
utilizing the zero vectors, the common-mode voltage
controlled by the proposedRCMV-MPC algorithms can
be restricted within ±Vdc/6. Furthermore, application of
the two nonzero vectors with optimal time sharing
between them can yield satisfactory load current ripple
performance without using the zero vectors. Thus, the
proposed RCMV-MPCmethods can reduce the common-
mode voltage as well as control the load currents with fast
transient response and satisfactory loadcurrent ripple
performance compared with the conventional model
predictive control method. Simulation and experimental
results areincluded to verify the effectiveness of the
proposed RCMV-MPC methods.
39. MATLAB2015_39 Interleaved Phase-Shift
Full-Bridge Converter With
Transformer Winding
Series–Parallel
The analysis and design guidelines for a two-phase
interleaved phase-shift full-bridge converter with
transformer winding series–parallel autoregulated current
doubler rectifier are presented in this paper. The
2015
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Autoregulated
(SPAR) Current Doubler
Rectifier
secondary windings of two transformers
work in parallel when the equivalent duty cycle is smaller
than 0.25but in series when the duty cycle is larger than
0.25 owing to theseries–parallel autoregulated rectifier.
With the proposed rectifying structure, the voltage stress
of the rectifier is reduced. Also, theinterleaving operation
reduces the output current ripple. A 1-kWprototype with
200–400-V input and 50-V/20-A output is built up
to verify the theoretical analysis.
40. MATLAB2015_40 Analysis of Active-
Network Converter with
Coupled
Inductors
High step-up voltage gain DC/DC converters are widely
applied in fuel cell stacks, photovoltaic arrays,
battery sources, and high intensity discharge (HID) lamps
power systems. Active-network converters with coupled
inductors (CL-ANC) are derived from switched inductor
active-network converters (SL-ANC). The proposed
convertercontains two coupled inductors which can be
integrated into one magnetic core and two power
switches. The convertercan provide a relatively high
voltage conversion ratio with a small duty cycle; the
voltage and current stress of powerswitches are low
which is helpful to reduce the losses. This paper shows
the key waveforms of the CL-ANC anddetailed derivation
of the steady-state operation principle. The voltage
conversion ratio and the effect of the leakage
inductance on voltage gain are discussed. The voltage
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stress and current stress on the power devices are
illustrated andthe comparison between the proposed
converter and SL-ANC are given. Finally, the prototype
has been established inthe lab with 200V and 400V
output under different turn ratios. Experimental results are
given to verify the correctnessof the analysis.
41. MATLAB2015_41 Modeling and Controller
Design of a Semi-Isolated
Multi-Input Converter for
Hybrid PV/Wind Power
Charger System
The objective of this paper is to propose the
development of a multi-input dc-dc converter (MIC)
family whichis composed of isolated and/or non-isolated
dc-dc converters. Byanalyzing five basic isolated dc-dc
converters, four isolatedpulsating voltage source cells (I-
PVSCs) and three isolatedpulsating current source cells
(I-PCSCs) are generated. Moreover,a semi-isolated multi-
input converter (S-MIC) for hybridPV/wind power
charger system which can simplify the power
system, reduce the cost, deliver continuous power and
overcomehigh voltage-transfer-ratio problems is
proposed. In this paper,the operational principle of the
proposed S-MIC is explained, thesmall-signal ac model is
derived and the controller design isdeveloped. Computer
simulations and experimental results arepresented to
verify the accuracy of the proposed small signal acmodel
and the performance of the proposed S-MIC.
2015
42. MATLAB2015_42 A Four-Switch Three- The four-switch three-phase (FSTP) inverterhas been 2015
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Phase SEPIC-Based
Inverter
proposed as an innovative inverter design to
reduce the cost, complexity, size, and switching losses of
the DC-AC conversion system. Traditional FSTP inverter
usually operates at half the DC input voltage, hence, the
output line voltage cannot exceed this value. This paper
proposes a novel design for the FSTP inverter based on
thetopology of the single-ended primary-inductance
converter(SEPIC). The proposed topology provides pure
sinusoidaloutput voltages with no need for output filter.
Comparedto traditional FSTP inverter, the proposed
FSTP SEPICinverter improves the voltage utilization
factor of the inputDC supply, where the proposed
topology provides higheroutput line voltage which can be
extended up to the fullvalue of the DC input voltage. The
integral sliding-modecontrol is used with the proposed
topology to optimize itsdynamics and to ensure
robustness of the system duringdifferent operating
conditions. Derivation of the equationsdescribing the
parameters design, components ratings, andthe operation
of the proposed SEPIC inverter is presentedin this paper.
Simulation model and experimental setupare used to
validate the proposed concept. Simulations
andexperimental results show the effectiveness of
theproposedinverter.
43. MATLAB2015_43 High-Efficiency Isolated
Single-Input Multiple-
This study presents a high-efficiency isolated single-input
multiple-output bidirectional (HISMB) converter for a 2015
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Output
Bidirectional Converter
power storage system. According to the power
management, the proposed HISMB converter can operate
at a step-up state (energy release) and a step-down state
(energy storage). At the step-up state, it can boost the
voltage of a low-voltage input power source to a high-
voltage-side dc bus and middle-voltage terminals. When
the high-voltage-side dc bus has excess energy, one can
reversely transmit the energy. The high-voltage dc bus
can take as the main power, and middle-voltage output
terminals can supply powers for individual middle-
voltage dc loads or to charge auxiliary power sources
(e.g., battery modules). In this study, a coupled-inductor-
based HISMB converter accomplishes the bidirectional
power control with the properties of voltage clamping and
soft switching, and the corresponding device
specifications are adequately designed. As a result, the
energy of the leakage inductor of the coupled inductor
can be recycled and released to the high-voltage-side dc
bus and auxiliary power sources, and the voltage stresses
on power switches can be greatly reduced. Moreover, the
switching losses can be significantly decreased because of
all power switches with zero-voltage-switching (ZVS)
features. Therefore, the objectives of high-efficiency
power conversion, electric isolation, bidirectional energy
transmission, and various output voltage with different
levels can be obtained. The effectiveness of the proposed
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HISMB converter is verified by experimental results of a
kW-level prototype in practical applications.
44. MATLAB2015_44 Modularized Control
Strategy and Performance
Analysis of DFIG System
under Unbalanced and
Harmonic Grid Voltage
The paper presents a modularized control
strategy of doubly fed induction generator (DFIG)
system,including the grid-side converter (GSC) and rotor-
sideconverter (RSC), under unbalanced and harmonic
gridvoltage. The sequence decomposition process
andcomplicated control reference calculation can be
avoidedin the proposed control strategy. From the
perspective ofpower grid friendly-operation, the control
targets of DFIGsystem in this paper are chosen as: 1)
smooth active andreactive power injected into the power
grid; 2) balancedand sinusoidal current injected into the
power grid. TheRSC and GSC can work as two
independent modules andthe communication between
RSC and GSC can beremoved. Furthermore, the 3rd
harmonic currentcomponent, DC link voltage fluctuation
andelectromagnetic torque pulsation under the different
control targets are theoretically analyzed. Finally, the
availability of the proposed modularized control strategy
of DFIG system under unbalanced and distorted grid
voltage is verified by experiment results.
2015
45. MATLAB2015_45 Resonant Switched-
Capacitor Voltage
A new, small and efficient voltage regulator,
realized using a resonant switched capacitor converter 2015
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Regulator with Ideal
Transient Response
technology, is introduced. Voltage regulation is
implemented by means of simple digital pulse density
modulation. It displays an ideal transient response with a
zero-order nature to all disturbance types. The newly
developed topology acts as a gyrator with a wide range of
voltage conversion ratios (below as well as above unity)
with constant efficiency characteristics for the entire
operation range. The operation of the voltage regulator is
verified on a 20W experimental prototype, demonstrating
ideal transient recovery without over/under-shoots in
response to load and line transients. Simple design
guidelines for the voltage regulation system are provided
and verified by experiments.
46. MATLAB2015_46 On the Performance of
Multiobjective
Evolutionary
Algorithms in Automatic
Parameter Extraction of
Power Diodes
In this paper, a general, robust, and automatic
parameter extraction of nonlinear compact models is
presented.The parameter extraction is based on
multiobjective optimizationusing evolutionary algorithms
which allow fitting of several highly
nonlinear and highly conflicting characteristics
simultaneously.Two multiobjective evolutionary
algorithms which have beenproved to be robust for a wide
range of multiobjective problems [1]–[3], the
Nondominated Sorting Genetic Algorithm II
and the Multiobjective Covariance Matrix Adaptation
EvolutionStrategy, are used in the parameter extraction of
2015
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a novel powerdiode compact model based on the lumped
charge technique.The performance of the algorithms is
assessed using a systematicstatistical approach. Good
agreement between the simulated and
measured characteristics of the power diode shows the
accuracyof the used compact model and the efficiency
and effectivenessof the proposed multiobjective
optimization scheme.
47. MATLAB2015_47 Development of a Wind
Interior Permanent-Magnet
Synchronous Generator
Based Microgrid and Its
Operation Control
This paper presents the development of a wind
interior permanent-magnet synchronous generator
(IPMSG)based DC micro-grid and its operation control.
First, thederated characteristics of PMSG systems with
various AC/DCconverters and operation controls are
comparatively analyzed.Then the IPMSG followed by
three-phase Vienna switchmode rectifier (SMR) is
developed to establish the commonDC bus of DC micro-
grid. Good developed power and voltageregulation
characteristics are achieved via the proposedcommutation
tuning, robust current and voltage controls.
Second, a single-phase three-wire (1P3W) inverter is
constructed to serve as the test load. Good AC
220V/110Voutput voltage waveforms under unknown
and nonlinearloads are preserved by the developed robust
2015
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waveformtracking control scheme. Third, a battery energy
storagesystem (BESS) is established, and the fast energy
storagesupport response is obtained via the proposed
droop controlapproach with adaptive predictive current
control method. Inaddition, a chopped dump load is
equipped to enhance theenergy balance control flexibility.
48. MATLAB2015_48 A Novel Drive Method for
High-Speed
Brushless DC Motor
Operating in a Wide
Range
In this paper, a novel drive method, which is different
from the traditional motor drive techniques, for high-
speedbrushless DC (BLDC) motor is proposed and
verified by a seriesof experiments. It is well known that
the BLDC motor can bedriven by either Pulse-Width
Modulation (PWM) techniques witha constant DC-link
voltage or Pulse-Amplitude Modulation (PAM)techniques
with an adjustable DC-link voltage. However, to ourbest
knowledge, there is rare study providing a proper drive
method for high-speed BLDC motor with a large power
over a widespeed range. Therefore, the detailed
theoretical analysis comparison of the PWM control and
the PAM control for high-speedBLDC motor is first
given. Then a conclusion that the PAM control is superior
to the PWM control at high speed is obtained
because of decreasing the commutation delay and high
frequencyharmonic wave. Meanwhile, a new high-speed
BLDC motor drivemethod based on the hybrid approach
combining PWM and PAMis proposed. At last, the
2015
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feasibility and effectiveness of the performance analysis
comparison and the new drive method areverified by
several experiments.
49. MATLAB2015_49 The Dynamic Control of
Reactive Power for the
Brushless Doubly Fed
Induction Machine with
Indirect Stator-quantities
Control Scheme
Compared to the doubly fed induction
machine (DFIM), the brushless doubly fed induction
machine (BDFIM) has higher reliability by virtue of the
absence of a brush gear. Recent research on structure
optimization design and control strategy of BDFIM has
made remarkable progress. BDFIM indirect
stator-quantities control (ISC) is a new control strategy,
which, in comparison to vector control strategy, requires
fewer parameters and does not need rotating coordinate
transformation. This paper further develops the dynamic
control of reactive power for the BDFIM with ISC
scheme.Detailed theoretical analysis is done to show the
controllerstructure of the reactive power. The
experimental resultsof the prototype show the feasibility
of the proposedscheme. As a result, the proposed ISC
controllers havebeen able to control not only speed and
torque, but alsothe reactive power.
2015
50. MATLAB2015_50 An LCL-LC Filter for
Grid-Connected
Converter: Topology,
Parameter and Analysis
In order to further cut down the cost of filter for
grid-connected pulse width modulation (PWM) converter
underthe more and more stringent grid code, a new kind
of high orderfilter, named LCL-LC filter, is presented in
2015
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this paper. Theresonant frequency characteristics of the
filter are analyzed anda parameter design method on the
base of the characteristics isalso proposed in the paper.
The proposed parameter designmethod can easily make
full use of the existing research resultsabout the
traditional LCL filter parameter design. And then a
parameter robustness analysis method based on
four-dimensional graphics is proposed to analyze
parameterrobustness of the presented filter. Compared
with the traditionalone, the proposed analysis method can
analyze the filterperformance under variations of several
parameters at a timewithout any iteration. The
comparative analysis and discussionconsidering the LCL
filter, the trap filter, and the LCL-LC filter,
are presented and verified through the experiments on a
5kWgrid-connected converter prototype. Experiment
resultsdemonstrate the accuracy of theoretical analysis
and prove thepresented filter has a better performance
than two others.
51. MATLAB2015_51 3D microtransformers for
DC-DC on-chip
power conversion
We address the miniaturization of power converters by
introducing novel, 3D microtransformers with magnetic
core forlow-MHz frequency applications. The core is
fabricated by lamination and microstructuring of
Metglas® 2714A magnetic alloy. Thesolenoids of the
microtransformers are wound around the core using a
2015
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ball-wedge wirebonder. The wirebonding process is fast,
allowingthe fabrication of solenoids with up to 40 turns in
10 s. The fabricated devices yield the high inductanceper
unit volume of 2.95 µH/mm3and energy per unit volume
of 133 nJ/mm3 at the frequency of 1 MHz. The power
efficiency of 64-76% are measured for different turnsratio
with coupling factors as high as 98%.
52. MATLAB2015_52 Indirect Matrix Converter-
Based Topology
and Modulation Schemes
for Enhancing
Input Reactive Power
Capability
A new topology based on indirect matrix converter
(IMC) is proposed to enhance the input reactive power
capability. This topology consists of a conventional IMC
and an auxiliaryswitching network (ASN), which is
connected to the dc-link of theIMC in parallel. With the
aid of ASN, an implicit current sourceconverter-based
static synchronous compensator can be embedded
into an IMC, which lays a foundation for the input
reactive powercontrol. Based on the proposed topology,
two modulation schemesare presented, and the formations
of the output voltage and input reactive current are
decoupled in both of them. To minimize
power loss and improve input current quality, a double
closed-loopcontrol algorithm is introduced, in which the
current through thedc inductor in ASN is controlled to be
minimum. Different fromthe conventional IMC, the input
reactive power of the topologyis independent of its load
condition without considering the practical constraints.
2015
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The effectiveness of the proposed topology
andmodulation scheme is confirmed by experimental
results.
53. MATLAB2015_53 Closed Loop Discontinuous
Modulation Technique
for Capacitor Voltage
Ripples and Switching
Losses
Reduction in Modular
Multilevel Converters
In this paper, a new discontinuous modulation
technique is presented for the operation of the modular
multilevelconverter (MMC). The modulation technique is
based on addinga zero-sequence to the original
modulation signals so that theMMC arms are clamped to
the upper or lower terminals of thedc-link bus. The
clamping intervals are controlled according to
the absolute value of the output current to minimize the
switchinglosses of the MMC. A significant reduction in
the capacitorvoltage ripples is achieved, especially when
operating with lowmodulation indices. Furthermore, a
circulating current controlstrategy suitable for this
modulation technique is also proposed.Simulation and
experimental results under various operatingpoints are
reported along with evaluation and comparison results
against a conventional carrier-based pulse-width
modulationmethod.
2015
54. MATLAB2015_54 Decentralized Inverse-
Droop Control for
Input-Series-Output-
Parallel DC-DC Converters
Input-series-output-parallel (ISOP) DC-DCconverters are
suited for high input-voltage and lowoutput-voltage
applications. This letter presents adecentralized inverse-
droop control for this configuration.Each module is self-
contained and no central controller isneeded, thus
2015
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improving the system modularity, reliabilityand
flexibility. With the proposed inverse-droop control,
the output voltage reference rises as the load becomes
heavy. Even though the input voltages is not used in the
inverse-droop loop, the power sharing including input
voltage sharing (IVS) and output current sharing (OCS)
can still be well achieved. Besides, the output voltage
regulation characteristic is not affected by the variation
of input voltage. The operation principle is introduced,
and stability of the strategy is also revealed based on
small signal modeling. Finally, the experiment is
conducted to verify the effectiveness of the control
strategy.
55. MATLAB2015_55 Detailed Analysis of DC-
Link Virtual Impedance
based Suppression Method
for Harmonics Interaction
in High-Power PWM
Current-Source Motor
Drives
For high-power PWM current-source motor drive
systems, due to the low converter switching frequency
and therelative small dc choke for reduced cost/weight,
the converters‘switching harmonics may interact through
dc link and produceinterharmonics in the entire system.
Such harmonics interactionphenomenon may give rise to
the system resonance at certainmotor speeds, which
degrades the grid-side power quality andgenerates
excessive torque ripples on the motor side. The resonance
caused by the harmonics interaction in high-power PWM
current-source motor drives is investigated in previous
work. Inaddition, to actively suppress such resonance, the
basic idea of adc-link virtual impedance based
2015
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suppression method has alsobeen proposed. This paper
extends the previous work to thoroughly analyze the
mechanism and realization of resonance suppression by
the dc-link virtual impedance based method. The indepth
analysis shows that the dc-link virtual impedance based
method successfully enables the active interharmonics
compensation capability of high-power PWM current-
source drives, whichis not addressed in previous
researches. Moreover, simulationsand experiments
demonstrate that, by following the selection ofcoefficient
in the suppression method discussed in this paper, the
dc-link virtual impedance based method can effectively
enhancethe attenuation effect of dc link in high-power
PWM currentsource drive systems so as to suppress the
resonance due to theharmonics interaction under all
resonance conditions.
56. MATLAB2015_56 An Online Frequency-
Domain Junction
Temperature Estimation
Method for IGBT Modules
This letter proposes a new frequency-domain
thermal model for online junction temperature estimation
ofinsulated-gate bipolar transistor (IGBT) modules. The
proposedmodel characterizes the thermal behavior of an
IGBT module bya linear time-invariant (LTI) system,
whose frequency response isobtained by applying the fast
Fourier transform (FFT) to the timederivative of the
transient thermal impedance from junction to a
reference position of the IGBT module. The junction
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temperatureof the IGBT is then estimated using the
frequency responses of theLTI system and the heat
sources of the IGBT module. Simulationresults show that
the proposed method is computationally efficient
for an accurate online junction temperature estimation of
IGBTmodules in both steady-state and transient loading
conditions.
57. MATLAB2015_57 Characterization of a
Silicon IGBT and Silicon
Carbide MOSFET Cross
Switch Hybrid
A parallel arrangement of a Silicon (Si) IGBT and a
Silicon Carbide (SiC) MOSFET is experimentally
demonstrated.The concept referred to as the Cross Switch
―XS‖ hybrid aims toreach optimum power device
performance by providing low staticand dynamic losses
while improving the overall electrical andthermal
properties due to the combination of both the bipolar Si
IGBT and unipolar SiC MOSFET characteristics. For the
purposeof demonstrating the XS hybrid, the parallel
configuration wasimplemented experimentally in a single
package for devices ratedat 1200V. Test results were
obtained to validate this approach withrespect to the static
and dynamic performance when compared to
a full Si IGBT and a full SiC MOSFET reference
deviceshavingthe same power ratings as for the XS hybrid
samples.
2015
58. MATLAB2015_58 LCL Filter Design and The harmonic filter for a 3-level neutral point 2015
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Inductor Current Ripple
Analysis for 3-
level NPC Grid Interface
Converter
clamped (NPC) grid interface converter is designed in this
paperwith good filtering performance and small
component size. LCLtopology is selected because of the
attenuation and size tradeoff.The design of the inverter
side inductor L1 is emphasized due toits cost. A detailed
inductor current ripple analysis is givenbased on the space
vector modulation (SVM). The analysisderives the
inductor volt-second and the maximum current
ripple equation in line cycle. It also reveals the switching
cyclecurrent ripple distribution over a line cycle, with the
consideration of power factor. The total system loss is
calculatedwith different ripple current. Inductor L1 is
determined by theloss and size tradeoff. Also the
capacitor and grid side inductorL2 is designed based on
attenuation requirement. Differentdamping circuits for
LCL filter are compared and investigatedin detail. The
filter design is verified by both simulation and a200kVA
3-level NPC converter hardware.
59. MATLAB2015_59 Virtual RC Damping of
LCL-Filtered Voltage
Source Converters with
Extended Selective
Harmonic Compensation
Active damping and harmonic compensation are
two common challenges faced by LCL-filtered voltage
source converters. To manage them holistically, this
paper begins byproposing a virtual RC damper in parallel
with the passive filtercapacitor. The virtual damper is
actively inserted by feeding backthe passive capacitor
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current through a high-pass filter, whichindirectly,
furnishes two superior features. They are the
mitigation of phase lag experienced by a conventional
damperand the avoidance of instability caused by the
negative resistanceinserted unintentionally. Moreover,
with the virtual RC damper,the frequency region, within
which the harmonic compensation iseffective, can be
extended beyond the gain crossover frequency.This is of
interest to some high-performance applications, but has
presently not been achieved by existing schemes.
Performance ofthe proposed scheme has been tested in
the laboratory withresults obtained for demonstrating
stability and harmoniccompensation.
60. MATLAB2015_60 Versatile Control of
Unidirectional AC-DC
Boost Converters for
Power Quality Mitigation
This paper introduces a versatile control scheme for
unidirectional ac-dc boost converters for the purpose of
mitigating grid power quality. Since most power factor
correctioncircuits available in the commercial market
utilize unidirectionalac-dc boost converter topologies, this
is an almost no-cost solutionfor compensating harmonic
current and reactive power inresidential applications.
Harmonic current and reactive power
compensation methods in the unidirectional ac-dc boost
converterare investigated. The additional focus of this
paper is to quantifythe input current distortions by the
unidirectional ac-dc boostconverter used for supplying
2015
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not only active power to the load butalso reactive power.
Due to input current distortions, the amountof reactive
power injected from an individual converter to the grid
should be restricted. Experimental results are presented to
validate the effectiveness of the proposed control method.
61. MATLAB2015_61 Aalborg Inverter — A new
type of ―Buck in
Buck, Boost in Boost‖
Grid-tied Inverter
This paper presents a new family of high
efficiency DC/AC grid-tied inverter with a wide
variation of input DC voltage. It is a ―Boost in Boost,
Buck in Buck‖ inverter, meaning that only one power
stage works at high frequency in order to achieve
minimum switching loss. The minimum voltage drop of
the filtering inductor in the power loop is achieved to
reduce the conduction power loss in both ―Boost‖ and
―Buck‖ mode. The principle of operation is
demonstrated through the analysis on the equivalent
circuits of a ―half-bridge‖ single-phase inverter. The
theoretical analysis shows that when input DC voltage
is larger than the magnitude of the AC voltage, it is a
Voltage Source Inverter (VSI), and on the contrary it is
Current Source Inverter (CSI) in the other mode. A
220 V/50 Hz/ 2000 W prototype has been constructed.
Simulations and experiments show it has a good control
and system performance.
2015
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62. MATLAB2015_62 Grid-connected Forward
Micro-inverter with
Primary-Parallel
Secondary-Series
Transformer
This paper presents a primary-parallel secondaryseries
multicore forward micro-inverter for photovoltaic
ACmodule application. The presented micro-inverter
operateswith a constant off-time boundary mode control,
providingMPPT capability and unity power factor. The
proposed multitransformer solution allows using low-
profile unitary turnsratio transformers. Therefore, the
transformers are bettercoupled and the overall
performance of the micro-inverter isimproved. Due to the
multiphase solution the number ofdevices increases but,
the current stress and losses per device
are reduced contributing to an easier thermal
management.Furthermore, the decoupling capacitor is
split among thephases, contributing to a low-profile
solution withoutelectrolytic capacitors suitable to be
mounted in the frame of aPV module. The proposed
solution is compared to the classicalparallel interleaved
approach, showing better efficiency in awide power range
and improving the weighted efficiency.
2015
63. MATLAB2015_63 A Single-Stage
PhotoVoltaic System for a
DualInverter fed Open-End
Winding Induction Motor
This paper presents an integrated solution for
PhotoVoltaic (PV) fed water-pump drive system, which
uses anOpen-End Winding Induction Motor (OEWIM).
The dualinverter fed OEWIM drive achieves the
2015
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Drive for Pumping
Applications
functionality of a threelevel inverter and requires low
value DC bus voltage. This helpsin an optimal
arrangement of PV modules, which could avoidlarge
strings and helps in improving the PV performance with
wide band-width of operating voltage. It also reduces the
voltagerating of the DC-link capacitors and switching
devices used in thesystem. The proposed control strategy
achieves an integration ofboth Maximum Power Point
Tracking (MPPT) and V/f controlfor the efficient
utilization of the PV panels and the motor. The
proposed control scheme requires the sensing of PV
voltage andcurrent only. Thus, the system requires less
number of sensors.All the analytical, simulation and
experimental results of thiswork under different
environmental conditions are presented inthis paper.
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MATLAB PROJECTS 2014
SN PROJECT
CODE
PROJECT TOPIC YEAR
1
MAT1425
Topic: Diagnosis of diabetic retinopathy by employingimage processing technique to detect exudates
inretinal images
Abstract: Diabetic retinopathy (DR) is a microvascular complication of long-term diabetes and it is the
major cause of visualimpairment because of changes in blood vessels of the retina. Major vision loss because
of DR is highly preventable withregular screening and timely intervention at the earlier stages. The presence of exudates is one of the primitive signs of DRand the detection of these exudates is thefirst step in
2014
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automated screening for DR. Hence, exudates detection becomes asignificant diagnostic task, in which digital retinal imaging plays a vital role. In this study, the authors propose an algorithmto detect the presence
of exudates automatically and this helps the ophthalmologists in the diagnosis and follow-up of DR.Exudates
are normally detected by their high grey-level variations and they have used an artificial neural network to performthis task by applying colour, size, shape and texture as the features. The performance of the authors
algorithm has beenprospectively tested by using DIARETDB1 database and evaluated by comparing the
results with the ground-truth imagesannotated by expert ophthalmologists. They have obtained illustrative results of mean sensitivity 96.3%, mean specificity99.8%, using lesion-based evaluation criterion and
achieved a classification accuracy of 99.7%.
2
MAT1424
Topic: Data Hiding in Encrypted H.264/AVC VideoStreams by Codeword Substitution
Abstract: Digital video sometimes needs to be stored andprocessed in an encrypted format to maintain
security andprivacy. For the purpose of content notation and/or tampering detection, it is necessary to
perform data hiding in theseencrypted videos. In this way, data hiding in encrypted domainwithout decryption preserves the confidentiality of the contentIn addition, it is more efficient without decryption
followed bydata hiding and re-encryption. In this paper, a novel schemeof data hiding directly in the
encrypted version of H.264/AVCvideo stream is proposed, which includes the following threeparts, i.e., H.264/AVC video encryption, data embedding, anddata extraction. By analyzing the property of H.264/AVC
codec,the codewords of intraprediction modes, the codewords of motionvector differences, and the
codewords of residual coefficients areencrypted with stream ciphers. Then, a data hider may embedadditional data in the encrypted domain by using codewordsubstitution technique, without knowing
the original video content. In order to adapt to different application scenarios, dataextraction can be done
either in the encrypted domain or in thedecrypted domain. Furthermore, video file size is strictly preserved even after encryption and data embedding. Experimentalresults have demonstrated the feasibility and
efficiency of theproposed scheme.
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
3
MAT1423
Topic: Edge Detection Method for Image Processingbased on Generalized Type-2 Fuzzy Logic
Abstract: This paper presents an edge detection method based on the morphological gradient
technique and generalized type-2 fuzzy logic. The theory of alpha planes is used to implement generalized type-2 fuzzy logic for edge detection. For the defuzzification process, the heights and
approximation methods are used. Simulation results with a type-1 fuzzy inference system (T1FIS), an
interval type-2 fuzzy inference system (IT2FIS) and with a generalized type-2 fuzzy inference system (GT2FIS) for edge detection are presented. The proposed generalized type-2 fuzzy edge detection method
was tested with benchmark images and synthetic images. We used the merit of Pratt measure to
illustrate the advantages of using generalizedtype-2 fuzzy logic.
2014
4
MAT1422
Topic: Deblurred images post-processingby Poisson warping
Abstract: In this work we develop a post-processing algorithm which enhances the results of the existing
image deblurringmethods. It performs additional edge sharpening using grid warping. The idea of the proposed algorithm is totransform the neighborhood of the edge so that the neighboring pixels move closer
to the edge, and then resamplethe image from the warped grid to the original uniform grid. The proposed
technique preserves image textures whilemaking the edges sharper. The effectiveness of the method is shown for basic deblurring methods on LIVE databaseimages with added blur and noise.
2014
5
MAT1421
Topic: Image Contrast Enhancement UsingColor and Depth Histograms
Abstract: In this letter, we propose a new global contrast enhancement algorithm using the histograms of
color and depth images. On the basis of the histogram-modification framework, thecolor and depth image
histograms arefirst partitioned into subintervals using the Gaussian mixture model. The positions partitioning
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
the color histogram are then adjusted such that spatiallyneighboring pixels with the similar intensity and depth values canbe grouped into the same sub-interval. By estimating the mappingcurve of the contrast
enhancement for each sub-interval, the globalimage contrast can be improved without over-enhancing the
localimage contrast. Experimentalresults demonstrate the effectiveness of the proposed algorithm.
6
MAT1420
Topic: Object Tracking Based on Active Contour Modeling
Abstract: Object Tracking based on Active Contour Modeling is an image processing based technology that uses snapshots of the object under consideration to track it via robot in the realworld. The objective has been
to implement a unique methodology that employs the pursuing and adapting of contour to the current state of
image, and hence track the object. Thesystem can be implemented in drone planes wherein this algorithm can be used to guide the movement of the gun based onthe movements of the object, or, in robot games with
a slightly more advanced robot. Initially Image Processing is performed to reduce operation complexity and
achieve swift real-time performance. A set of contour-based modeling algorithms is then implemented to ‗actively‘ track the subject. Also, relative
transformation calculations are made to lock the target via robot,continuously. MATLAB is used to simulate
and implement the system and it is tested on field with a ball placed on it and a robot tracking the ball. The experiments prove that the system successfully detects and tracks the object efficiently in the real world for
all horizontal and vertical transitions.
2014
7
MAT1419
Topic: Vision Based Data Extraction of Vehicles in Traffic
Abstract: With the rise in traffic related crimes the needfor an efficient automated surveillance system has become ofutmost importance. This paper proposes a system to monitorvideo from traffic cameras and
process it in real time forstoring essential information of the vehicles in traffic. Histogramof Oriented
Gradients (HOG) of extracted frames is used asfeatures for classification (vehicle frame and non vehicle
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
frame).The classifier is designed based on Support Vector Machine(SVM) . The subtracted image acquired from a dynamicallyupdated background image is used to extract the vehicle imagefor recognition using
trained Artificial Neural Network(ANN).The system is designed to store details like vehicle make,
model,color and time of passing the camera in a database (MicrosoftAccess (MS Access)). Finally the stored details are made availablethrough a Graphical User Interface(GUI) designed using VisualBasic(VB) that will
provide an user with the options of selectinga time window to look for the vehicles that have passed
withinthat interval or to enter a car model to check if it has passed thatpoint at any time. The system is modeled in MATLAB and testedin a real time environment in one of the busiest road in Kamrupdistrict of
Assam and provides satisfactory performance.
8
MAT1418
Topic: Digital Right Management Control for Joint Ownership of Digital Images using Biometric
Features
Abstract: This paper proposes a method to establish joint ownership of digital images by embedding imperceptible digital pattern in the image. This digital pattern is generated frombiometric features of more
than one subject in a strategic matter so that the identification of individual subject can be done and the
multiple ownership of the digital images can be established. This digital pattern was embedded and extracted from the image and the experiments were also carried out when the image was subjected to signal processing
attacks. Coefficients of mid frequency band discrete cosine transform was used for
embedding as these coefficients do not adversely affect the perceptual transparency and is also significantly robust to normal signal processing attacks. Experimental results indicate that the insertion of this digital
pattern does not change the perceptual properties of the image and the pattern survives
signal processing attacks which can be extracted for unique identification.
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
9
MAT1417
Topic: Intelligent Water Metering System: An Image Processing Approach (MATLAB simulations)
Abstract: The scarcity and misuse of fresh water pose a serious and growing threat to sustainable
development. The population growth, severe droughts and uneven distribution of water resources are the
reasons for water scarcity, and this scarcity will only continue to grow more severe. The technical sophistication of meters for measuring water flows has increased noticeably in recent decades in order to
improve management of water. This paper proposes simple image processing approach for an intelligent
metering system. The proposed system uses simple image processing algorithms and DSP processor, capable of executing MIPS; which makes whole system respond faster. As meter image is being captured from set
distance, meter mask generation reduces the need of algorithms for detection and segmentation of meter
reading. The proposed system improves the efficiency of drinking water management and reduces power consumption as image sensor is activated as per predefined billing cycle.
2014
10
MAT1416
Topic: Fingerprint Recognition Using Gabor Filter
Abstract: Fingerprint recognition is the most popular methods used for identification with higher degree of
success. The fingerprint has unique characteristics called minutiae, which are points where a curve track finishes, intersect or branches off. In this work a method for Fingerprint recognition is considered using a
combination of Fast Fourier Transform (FFT) and Gabor Filters forenhancing the image. The proposed
method involves combination of Gabor filter and Frequency domain filtering for enhancing the fingerprint. With eight different orientations of Gabor filter, features of the fingerprint
extracting are combined. In Frequency domain filtering, the fingerprint image is subdivided into 32*32 small
frames. Features are extracted from these frames in frequency domain. Final enhanced fingerprint is obtained
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
with the results of Gabor filter and frequency domain filtering. Binarization and Thinning follows next where the enhanced fingerprint is converted into binary and the ridges are thinned to one pixel width. This
helps in extracting the Minutiae parts (ridge bifurcation and ridge endings). The overall recognition rate for
the proposed method is 95% which is much better than histogram method where the recognition rate is 64%. This project is implemented in MATLAB.
11
MAT1415
Topic: ARIMA Model based Breast Cancer Detection and Classification through Image Processing
Abstract: Computer Aided Diagnosis (CAD) has changed theway of medical diagnostics. As similar to other walk of diagnostics field, CAD is having high potential in breast cancer prognosis because of its
highest accuracy. CAD may play a very important role in developing countries i.e. EIT-MEM
(ElectricalImpedance Tomography –Multi-frequency Electrical Impedance Mammography) device being used for breast cancer defection.MEM-EIT produces tomography based mammograms which are
considered most reliable method of early detection of breast cancer. Cancer diagnostic expert all over the
world find this noninvasive technique very accurate as it is one dimensional representation of images in terms of temperature however the accuracy is limited and investigator fail to take into account the spatial co-
ordination between the pixels which is crucial in cancerous tumour detection and their classification
(cancerous or normal) in EIT (Electrical Impedance Tomography) - based mammogram images. In this study, we are trying to focus an algorithms based CAD (Computer Aided Diagnosis) model for tumour
detection and classification. We model it by ARIMA model (autoregressive integrated moving average
(ARIMA) model) and parameter estimation will be performed using leassquare method. Our system classifies the tumour into three categories- (i) healthy tissue (ii) benign tissue (iii) cancerous tissue along
with above three segments the performance analysis
between 2D image and 1D image will be done for better accuracy and sensitivity detection.
2014
12
MAT1414
Topic: Human Hand Image Analysis Extracting Finger Coordinates and Axial Vectors
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
Abstract: This paper presents a finger cut-off algorithm for accurate calculation of fingertip coordinates based on hand contours. It provides not only information on exact fingertip position but also orientation and
lengths of all fingers in the image. Algorithm can be used for development of user interfaces based on human
gesture analysis, such as TouchTable, multimodal gesture based user interface developed by the author. Advantages of proposed algorithm over fingertip detection algorithm originally used in TouchTable are
described.
13
MAT1413
Topic: Automatic Brain Tumor Detection and Segmentation in MR Images
Abstract: The MRI or CT scan images are primary follow up diagnostic tools when a neurologic exam
indicates a possibility of a primary or metastatic brain tumor existence. The tumor tissue mainly appears in brighter colors than the rest of the regions inthe brain. Based on this observation, an automated algorithm for
brain tumor detection and medical doctors‘ assistance in facilitated and accelerated diagnosis procedure has
been developed and initially tested on images obtained from the patients with diagnosedtumors and healthy subjects.
2014
14
MAT1412
Topic: RGB ratios based skin detection
Abstract: Many different applications like face/people detection, image content interpretation, de-
identification for privacy protection in multimedia content, etc. requires skin detection as a pre-
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
processing step. There is no a perfect solution for skin detection, since this process is a compromise on speed, simplicity and precision (detection quality). There are many different techniques for skin
detection modeling ranging from simple models based on one or several thresholds to advanced
models based on neural network, Bayesian classifier, maximum entropy, k-means clustering, etc. This paper proposes a simple model, based on ratios of red, green and blue components of the RGB color
model. It describes how to make a compromise in a skin detection modeling by using three levels of
rules. Data analysis that supports conclusions is performed on the dataset from Universidad de Chile (UChile, dbskin2 –complete set) that contains 103 images and their annotations.
15
MAT1411
Topic: Embedding of Sound Clips as a Watermark in StilI Images using Discrete Wavelet Transform
Abstract: Embedding uj‘sndkr im+ys in Iarger images ming the oppmach of watermarking is being efecfively iised ,for image scvutinv. Wirh che advent of digital image processing; secure addition of
wutwmah in digitized images ming varivirs techtiiqzies has evolved, The me of wavelet transform for the
said pz~ipose has pw ved wry usefit/. This puper presenis a preliminary research carried out to embed audio clips in still images. The technique uses audio puperties aiidfirral disrortiun tfrreshold in the furget image
us parameters-for decision moking,fiw various aspects of the iinplemenfed scheme. Some of these decisions
ure selection oJ either grav scale or color images, decomposition level for the wavelet tmnsfbrni, chanvlel selection, sound sample and synrhwis of [he sound sample into minsamples. The research i.y
being exfended ,fbr embedding of audio samples in image sequences for video transmissions jbr .secwe
artdio commzrnication applicalions
2014
16
MAT1410
Topic: Automatic brain tumor detection and segmentation for MRI using covariance and
geodesic distance
Abstract: In this paper, we present a new approach that allows the detection and segmentation of
brain tumors automatically. The approach is based on covariance and geodesic distance. The
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
detection of central coordinates of abnormal tissues is based on the covariance method. These coordinates are used to segment the brain tumor area using geodesic distance for Tl and T2
weighted magnetic resonance images (MRI). The ultimate objective is to retrieve the attributes of the
tumor observed on the image to use them in the step of segmentation and classification. The present methods are tested on images of Tl and T2 weighted MR and have shown a better performance in
the analysis of biomedical images.
17
MAT1409
Topic: ANALYSIS OF RETINAL BLOOD VESSELS USING IMAGE PROCESSING
TECHNIQUES
Abstract: Assessment of blood vessels in human eye allows earlier detection of eye diseases such as
glaucoma and diabetic retinopathy. Digital image processing techniques play a vital role in retinal blood vessel detection , Several image processing methods and filters are in practise to detect and extract the
attributes of retinal blood vessels such as length ,width, pattern and angles. Automated Digital image
processing techniques and methods has to undergo more of improvisation to achieve precise accuracy to study the condition of Retinal Vessels especially in cases of Glaucoma and retinopathy; we have explained
various Templates based matched filters, Thresholding Methods, Segmentation methods, and functional
approaches to isolate the blood vessels.
2014
18
MAT1408
Topic: Automatic Optic Disc Detection in Digital Fundus Images Using Image Processing
Abstract: Optic disc (OD) is an important part of the eye. OD detection is an important step in
developing systems for automated diagnosis of various serious ophthalmic diseases like Diabetic
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
retinopathy, Glaucoma, hypertension etc. The variation of intensity within the optic disc and intensity close to the optic disc boundary are the major hurdle in automated optic disc detection. General edge
detection algorithms are frequently unsuccessful to segment the optic disc because of this. Complexity
increases due to the presence of blood vessels. This paper presents simple method for OD segmentation by using techniques like principal component analysis (PCA), mathematical morphology and
Watershed Transform. PCA used for good presentation of input image and mathematical morphology
is used to remove blood vessels from image. Watershed Transform is used for boundary segmentation.
19
MAT1407
Topic: A Comparative Analysis of Edge and Color Based Segmentation for Orange Fruit
Recognition
Abstract: In this paper, we presented two segmentation methods. Edge based and color based detection methods were used to segment images of orange fruits obtained under natural lighting
conditions. Twenty digitized images of orange fruits were randomly selected from the Internet in
order to find an orange in each image and to determine its location. We compared the results of both segmentation results and the color based segmentation outperforms the edge based segmentation
in all aspects. The MATLAB image processing toolbox is used for the computation and comparison
results are shown in the segmented image results.
2014
20
MAT1406
Topic: Detection of Leukemia in Microscopic Images Using Image Processing
Abstract: Leukemia occurs when lot of abnormal white blood cells produced by the bone marrow.
Hematologist makes use of microscopic study of human blood, which leads to need of
methods, including microscopic color imaging, segmentation, classification and clustering that can allow identification of patients suffering from Leukemia. The microscopic images will be inspected
visually by hematologists and the process is time consuming and tiring. The automatic image
processing system is urgently needed and can overcome related constraints in visual inspection.The
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
proposed system will be on microscopic images to detect Leukemia. The early and fast identification of Leukemia greatly aids in providing the appropriate treatment. Initial
segmentation is done using Statistical parameters such as mean, standard deviation which segregates
white blood cells from other blood components i.e. erythrocytes and platelets. Geometrical features such as area, perimeter of the white blood cell nucleusis investigated for diagnostic prediction of
Leukemia. The proposed method is successfully applied to a large number of images, showing
promising results for varying image quality.Different image processing algorithms such as Image Enhancement, Thresholding, Mathematical morphology and Labelling are implemented using LabVIEW
and MATLAB.
21
MAT1405
Topic: Lung Cancer Diagnosis Using CT-Scan Images Based on Cellular Learning Automata
Abstract: Lung cancer has killed many people in recent years. Early diagnosis of lung cancer can help
doctors to treat patients and keep them alive. The most common way to detect lung cancer is using the
Computed Tomography (CT) image. The systems that are created by the integration of computers and medical science are called Computer Aided Diagnosis (CAD). A CAD system that is adopted for the
diagnosis lung cancer, uses lung CT images as input and based on an algorithm helps doctors to perform an
image analysis. With the help of CAD, doctors can make the final decision. This paper is a study concerning automatic detection of lung cancer by using cellular learning automata. Images include some unwanted data
and some feature that are important for processing; pre-processing improves images by removing distortion
and enhance the important features. This system used lung CT scan so we applied some pre-processing method such as Gabor filter and region growing to improve CT
images. After pre-processing step according features the lung cancer nodule was extracted. The obtained
image through previous steps was entered to cellular learning automata lattice for training and making them possess the ability to detect lung cancer. The obtained results show, the proposed approach can reduce the
error rate.
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
22
MAT1404
Topic: Image Processing Based Vehicle Detection and Tracking Method
Abstract: Vehicle detection and tracking plays an effective and significant role in the area of traffic
surveillance system where efficient traffic management and safety is the main concern. In this paper, we discuss and address the issue of detecting vehicle / traffic data from video frames. Although various
researches have been done in this area and many methods have been implemented, still this area has room
for improvements. With a view to do improvements, it is proposed to develop an unique algorithm for vehicle data recognition and tracking using Gaussian mixture model and blob detection methods. First, we
differentiate the foreground from background in frames by learning the background. Here, foreground
detector detects the object and a binary computation is done to define rectangular regions around every detected object. To detect the moving object correctly and to remove the noise some morphological
operations have been applied. Then the final counting is done by tracking the detected objects and their
regions. The results are encouraging and we got more than 91% of average accuracy in detection and tracking using the Gaussian Mixture Model and Blob Detection methods.
2014
23
MAT1403
Topic: Image Encryption Based On Diffusion Process AndMultiple Chaotic Maps
Abstract: In the modern world, security is a prime importantissue and encryption is one of the preeminent
way to ensuresecurity. There are many image encryption schemes. Each one ofthem has its own strength and weakness. This project presents anovel algorithm for the image encryption and decryption scheme.The
project provides a secured image encryption technique usingmultiple chaotic based circular mapping. In this,
first, a pair ofsub keys is given by using chaotic logistic maps. Second, theimage is encrypted using logistic
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
map sub key and itstransformation leads to diffusion process. Third, sub keys aregenerated by four different chaotic maps. Based on the initialconditions, each map may produce various random numbersfrom various
orbits of the maps. Among those random numbers,
a particular number are selected as a key for the encryptionalgorithm. Based on the key, a binary sequence is generated tomanage the encryption algorithm. The input image of 2-D istransformed into a 1- D array by
using raster scanning. It is thendivided into various sub blocks. Then the position permutation isapplied to
each binary matrix based on multiple chaotic maps.Finally the receiver uses the same sub keys to decrypt theencrypted images. Also using the same encryption and decryptionalgorithm video is encrypted and
decrypted. Finally shown thatvideo encryption and decryption takes more time. Histogramanalysis,
correlation analysis are also done and found that thereis no statistical similarity between original and encrypted image.Peak Signal to Noise ratio is also calculated and found that theencrypted image is of higher
quality.
24
MAT1402
Topic: Real-time Vehicle Color Identification for Surveillance Videos
Abstract: Vehicles are one of the main detection targets of the traffic and security video surveillance
system. In this paper, we propose an automatic vehicle color identification method for vehicle classification.
The main idea of the proposed scheme is to divide a vehicle into a hierarchical coarse-to-fine structure to extract its wheels, windows, main body, and other auto parts. In the proposed method, the main body
alone is used by a support vector machine (SVM) for classification. Experimental results show that the
proposed scheme is efficient and effective and the proposed vehicle color identification is suitable for real-time surveillance applications.
2014
25
MAT1401
Topic: Intelligent Water Metering System: An Image Processing Approach (MATLAB simulations)
Abstract :The scarcity and misuse of fresh water pose a serious and growing threat to sustainable
development. The population growth, severe droughts and uneven distribution of water resources are the
2014
BULK MATLAB IEEE TITLES 2015-16
PONDICHERRY BRANCH Technos Inc.,II nd Floor, Natesan Tower, 100 FEET ROAD, PUDUCHERRY, 605 005 CT: +91 9566492473, +91 9585338678. E-MAIL: [email protected] , www.technosinc.blogspot.com , www.technosinc.page.tl
VILLUPURAM BRANCH
Technos Inc., Pondy Main Road, Koliyanur, Villupuram.605103 CT: +919942340236, +919444340236. E-MAIL:[email protected] www.technosinc.blogspot.com , www.technosinc.page.tl
Project Cost Starting Range Rs 1,500 for Clients with Full Documentation with Complete 24*7 Online Support
reasons for water scarcity, and this scarcity will only continue to grow more severe. The technical sophistication of meters for measuring water flows has increased noticeably in recent decades in order to
improve management of water. This paper proposes simple image processing approach for an intelligent
metering system. The proposed system uses simple image processing algorithms and DSP processor, capable of executing MIPS; which makes whole system respond faster. As meter image is being captured from set
distance, meter mask generation reduces the need of algorithms for detection and segmentation of meter
reading. The proposed system improves the efficiency of drinking water management and reduces power consumption as image sensor is activated as per predefined billing cycle.