Security System Using Motion Sensing Pptslides

8/4/2019 Security System Using Motion Sensing Pptslides

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Guided byProf. S.R.Kinge

Project by1.Omprakash Rai [B-3383067]2.Refad Shivani [B-3383096]3.Varun Agarwal [B-3383103]

SECURITY SYSTEM USING MOTIONSENSING



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Introduction



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ØThe moment we step out of our shopwe have a fear that someone would be

planning to stole our precious saving

and investments.

ØWe wish to make a full proof securitysystem that will provide tension freeenvironment for the same.



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ØIn today's times the extent of robberiesof valuable equipment has gone up to a

great extent.

Ø Thus due to the failure of such securitysystems we studied about anddeveloped our own concept of securitysystem where in we try to cover allbases possible to safeguard the

equipment

MOTIVATION FOR THE

PROJECT



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Literature Survey



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WHAT IS

SECURITY ?

ØFORM OF PROTECTION

ØHOWEVER SECURITY SYSTEMSAVAILABLE TODAY INSUFFICIENT

ØTHUS WE PRESENT TO YOU OUR SECURITY SYSTEM



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TYPES OF SECURITY SYSTEMS

ØLOCK ØSAFETY DEPOSIT BOXØMETAL DETECTOR ØBIOMETRIC SECURITY SYSTEMØPERIMETER SECURITY SYSTEMØ

AUTODIALLER ALARMØMULTIMETER WAVE SCANNER



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TECHNOLOGY USED IN SECURITYSYSTEMS

Ø RADAR

ØMOTION SENSING

ØPASSIVE INFRARED SENSORS

ØULTRASONIC SENSOR

ØMICROWAVE SENSOR



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TYPES OF MOTION SENSORS

Ø INFRARED SENSOR

ØMICROWAVE SENSOR

ØDIGITAL CAMERA



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CAUSE

One picture is worth more

than thousand words

WHY USING DIGITAL

CAMERA?



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SOFTWARES AVAILABLE

Ø MATLAB

ØTURBO C

Ø

JAVA

ØLabVIEW



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WHY MATLAB?

Ø EASY TO UNDERSTAND

ØSIMPLE TO USE

ØEASILY AVAILABLE



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Block Diagram

BMPFILE

EXTRACTING FEATURESOF IMAGE

COMPARINGFEATURESOF IMAGE WITHDATABASE

FEATURESFROMDATABASE

INITIATE A CALLOR A ALARM

CAMERA



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COMPONENTS USED

Camera

ØIR CAMERAØ1.3 Megapixels



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MIDDLEWARE

(PC , LAPTOP)

WHY A PC AND WITH

WHAT SPECIFICATIONS?

ØEASILY AVAILABLEØPOWERFUL PROCESSOR Ø

EASY TO USEØEXTRA CAMERA-USB 2.0



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BUZZER/ALARM

ØBuzzer with high frequency output

GSM MODULE



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Workin

gØImage Acquisition

ØBMP file format

Ø various filters we intend to use

ØExtracting information fromhistogram

ØV ri l rithm t nh n



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A digital image is a representation of atwo-dimensional image as a finite set of digital values, called picture elements orpixels

Image

Acquisition



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1 pixelPixel values

typically representgray levels, colors,heights, opacitiesetc

In digitalization thereare approximation of a real image



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BMP fileformat

Image formats include:1 sample per point (B&W or Grayscale)3 samples per point (Red, Green, and Blue)4 samples per point (Red, Green, Blue, and “Alpha”,a.k.a. Opacity)

For this project we will focus on grey-scale images



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Ø Given an image,recognize(identify) objects

Ø The hard part: the same object can look

incredibly different in different images dueto differences in view points, illumination,color, occlusions,… etc.

Ø A robust recognizer must develop invariantrecognition (translation, size, rotation?)

NATURE OF THE PROBLEM



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Static

Camera

MobileCamera

Dt(x,y)=|I1(x,y)−I2(x,y)|

Cami

Cami

Dt(x,y)=|I1(x,y)

−I2(x,y)|

V

AdaptiveThreshold

(x,y) = 1if

Dt(x,y) >Th

=0otherwise

Tht.

ChangeDetection

Multi-CameraRegistration

Chang

eDetection

ChangeDetection

ImageAcquisition

ImageAcquisition

CamerasCalibration

Cam 1

Cam n

Ref. IEEE SIGNAL PROCESSING

M ti D t ti U i Diff ti l



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Motion Detection Using DifferentialHistogram Equalization



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ac groun e ec on on



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ac groun e ec on onbasis of two frames

Ø The algorithm of two-frame-based B/F detectionis described below.

Ø f I: A pixel in a current frame, where I is theframe index.

Ø f I-1 : A pixel in a previous frame ( f I and f I-1 atthe same location.)

d I=

|f I - f I-1|

Bi = 1if bi>th.

else= 0

if bi<th.



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q The OriginalImage

q

The result of difference of two

Ø d I: Absolute difference of f Iand f I-1 . d I= |f I - f I-1 |

Øb I : B/F mask - 0: background.0xff: foreground.

Ø T: Threshold value.

ØIf d I > T, f I belongs to theforeground; otherwise, itbelongs to the background.



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ØAfter Differential

HistogramEqualization

Ø The result of adaptivethresholding



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qParticleremoving

q Motion boundary

ØThe some simple and smallnoise which is remained can be

removed by morphological processing

Ø It is done by two stages of Morphology algorithm(Dilation/Erosion)

Ø uniform and binary region of the movingobject will be achieved byusing the filling algorithm



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q Firstmovingobject

q Secondmovingobject

ØIt is not necessary to transmit the entireimage.

ØWe just extract the

moving images from the boundary thatwas obtained.

ØFinally, extracted images from

moving object are sent through LANand/or Modem toCentral Security System.



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ADVANTAGES

ØAutomatic security system

ØEasily installableØgood efficiency for fast detectionØLow maintenance cost

ØEasy to operateØUser helpfullyØReduce burden of operator



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ØUsed in high security areas like

bordersØSecurity of a MansionØUsed in museumØ Used in mall and shops

Application



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Future Scope

ØWith the help of a stereo photogrammetriccamera it can be mounted on vehicles as a

combination of hardware and software toavoid accidents by motion sensingØIt can be used in automationØWe can be used GSM module in it.

ØIn high security areas we can use facerecognition.ØWe can used gesture recognition with it.



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Security of a Mansion



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Current Status Of The Project

Ø We are done with literature survey and synopsisØWe have understood the various requirements todevelop a full proof security areasØ

We have carried out an extensive literaturesurveyØWe have studying most of the algorithms.ØWe have studied books like gonzalez and sonkaØWe have also studies projected related IEEE papers



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REFERENCES BOOKS

“Digital Image Processing”, RafaelC.

Gonzalez & Richard E. Woods,

“Digital Image Processing”

Sanka



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REFERENCES

ØMotion Detection Using Differential HistogramEqualizatioR. Hasanzadeh P.R.*, A. Shahmirzaie**, A.H. Rezaie***Electrical Engineering Department, Amirkabir University of Technology, Hafez Avenue,15914, Iran.

0-7803-9314-7/05/©2005 IEEE

ØMotion Tracking with an Active CameraDon Murray and Anup Basu, Member, IEEE

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND

MACHINE INTELLIGENCE. VOL. 16, NO. 5, MAY 1994

ØActive Video-Based Surveillance SystemIEEE SIGNAL PROCESSING MAGAZINE [25] MARCH 2005Gian Luca Foresti, Christian Micheloni,

Lauro Snidaro, Paolo Remagnino, and Tim Ellis



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Thanking

you

Documents

Security System Using Motion Sensing Pptslides