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7/30/2019 Architectural Model of Robot Vision System Smart Card Technology
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ARCHITECTURAL MODEL OF ROBOT
VISION SYSTEMSMART CARD
TECHNOLOGY
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ABSTRACT:
Technological advancement is widening up by the advent of new inventions.
Robot is one such invention to overcome the ever-present challenges of high cost of
labor, third world combination, and consumer demand for higher quality and greater
variety at a lower cost. It is an interdisciplinary field that ranges in scope from the
design of mechanical and electrical components to sensor technology, computer
systems, and artificial intelligence. It is the Science of designing and building robots
suitable for real life applications in manufacturing and other non-manufacturing
environment. In non-manufacturing environment robots act as computer-controlled
camera that allows it to see its environment and respond accordingly is known as its
vision.
In the current scenario, the Robot Vision System is basically used for
inspection purposes in Industries such as gauging, verification of presence of
components, detection of flaws, etc In this paper we have designed an architectural
model of Robot Vision System, by integrating it with Smart Card. Some of the
advanced features of the model are identifying the speeding vehicle, vehicles that are
not in proper lanes, reporting and sending the details of the vehicle to nearby Control
Station along with the particulars of the vehicle are the hallmarks of the designed
system. To avoid the unauthorized use of National Highways, we have introduced a
simple chip incorporated into the Robot Vision System. The main aim of our paper
is to protect valuable human lives. This advanced Smart Card and Robotic
Sensors System helps to avert accidents and damage to public property in future.
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1 INTRODUCTION:
1.1 MACHINE VISION SYSTEM:
Machine Vision can be defined as acquisition of image data followed by
processing and interpretation of data by using computer for some useful applications.
The Machine Vision System is generally classified as Two Dimensional and Three
Dimensional System. Generally, Three Dimensional is more advantageous, but
anyhow Two Dimensional System is much preferred for simple applications. The
general applications of Machine Vision System are dimension measuring, gauging,
verifying presence of components (flaws), and checking flatness of surface.
Decision
Camera and
Actions
Illumination
Object
Fig 1:Functioning of Machine Vision System
DIGITIZATION COMPUTERPROCESSING
IMAGEINTERPRETATION
ANALYSISPROGRAM
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1.1.1 IMAGE ACQUISITION AND DIGITIZATION:
Image Acquisition and Digitization is accomplished using a video camera and
a digitizing system to store the image data for subsequent analysis. The camera is
focused on the object of interest or the subject of interest and the image is obtained by
dividing the viewing area into a matrix of discrete picture elements called pixels, in
which each element has a value that is proportional to the light intensity of that
portion of the scene.
The intensity value for each pixel is converted into its equivalent digital value by an
ADC (Analog to Digital Converter).
Two types of Vision System:
1. Binary Vision:In Binary Vision the light intensity of each pixel is ultimately reduced
to either of two values, black or white, depending on whether the light
intensity exceeds a given threshold level.
2. Gray Scale Vision System:Gray Scale Vision System is a more sophisticated vision system, which
is capable of distinguishing and sorting different shades of gray in the image
depending on the intensity level. This type of system can determine not only
an objects outline and area characteristics, but also its surface characteristics
such as texture and color. Gray Scale Vision System typically uses 4, 6 or 8
bits of memory.
Each set of digitized pixel value is referred to as a frame. Each frame
is stored in a computer memory device called as frame buffer. The process of
reading all the pixel values in a frame is performed with the frequency of
30 times per second.
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Types of camera:
The two types of cameras that are used in Machine Vision applications
are:
1. Vidicon Camera:Vidicon Cameras are operated by focusing the image onto a
photoconductive surface and scanning the surface with an electron beam to
obtain the relative pixel values.
2. Solid State Camera:Solid State Cameras are operated by focusing the image on to 2
Dimensional array of very small, finely spaced photosensitive elements which
form the matrix of pixels. An electrical charge is generated by each element
according to the intensity of light striking the element. The charge is
accumulated in a storage device consisting of an array of storage elements
corresponding one to- one with a photosensitive picture element. These
charge values are read sequentially in the data processing and analysis
function of Machine Vision.
ILLUMINATION:
The scene viewed by the vision camera must be well illuminated, and
the illumination must be constant over the time. This almost always requires
the special lighting to be installed for Machine Vision applications rather than
rely on ambient lighting in the surroundings.
Types of Illumination:
1. Front Lighting:2. Back Lighting:3. Side Lighting:4. Structured Lighting using a planar sheet of light:5. Strobe Lighting:I
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1.1.2 IMAGE PROCESSING AND ANALYSIS:
The second function in the operation of Machine Vision System is
Image Processing and Analysis. The data that must be processed is significant
and the data for each frame must be analyzed within the time required to
complete one scan (1/30 second). A number of techniques have been
developed for analyzing the image data in Machine Vision System. The two
categories in Image Processing and Analysis are:
1. Segmentation:Segmentation techniques are intended to define and separate
regions of interest within the image. Two of the common segmentation
techniques are thresholding and edge detection.
Thresholding involves the conversion of each pixel intensity
level into a binary value, representing either whit or black. This is done by
comparing the intensity value of each pixel with defined threshold value. If
the pixel value is greater than the threshold, it is given the binary bit value of
white, say 1; if less than the defined threshold, then it is given the bit value of
black, say 0.
Edge detection is concerned with determining the location of
boundaries between an object and its surroundings in an image. This is
accomplished by identifying the contrast in light intensity that exists between
adjacent pixels at the borders of the object. A number of software for
algorithms has been developed for following the border around the object.
2. Feature Extraction:Most of the Machine Vision System characterizes an object in
the image by means of the objects features. Some of the features of an object
include the objects area, length, width, diameter, perimeter and center of
gravity. Feature Extraction method are designed to determine these features
based on a area and boundaries of the objectInfos
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1.1.3 INTERPRETATION:
The interpretation function is usually concerned with recognizing the
object, a task termed object recognition or pattern recognition. The objective
in these tasks is to identify the object in the image by comparing it with
predefined models. Two commonly used interpretation techniques are:
1. Template Matching:Template Matching is the name given to various methods that
attempt to compare one or more features of an image with the corresponding
features of a model or templates stored in computer memory. The most basic
template matching technique is one in which the image is compared, pixel-by-
pixel, with the corresponding computer model.
2. Feature Weighting:
Feature Weighting is a technique in which several features such
as area, length, perimeter, etc are combined into a single measure by
assigning a weight to each feature according to its relative importance in
identifying the object. The score of the object in the image is compared with
the score of an ideal object residing in computer memory to achieve proper
identification.
1.2 SMART CARD TECHNOLOGY:
Smart Card is a technological advancement, which has the potential to
make a significant impact on the quality of human life. It is manufactured
using Semi Conducting and Magnetic Materials.
There are two types of Smart Cards namely Contact Smart Cards for
which a Smart Card reader is required, and the Contact-less Smart Cards,
which can be waved in front of Sensors and used accordingly. This type of
Smart Card is very useful for Mass Transit and applications where large
number of movement of people happen very quickly and frequently. The main
applications of these Smart Cards are data carrier and identification.
.
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1.3 ENCODERS:
One of the most widely used position sensors is the optical encoder.
Capable of resolutions that are more than adequate for robotic applications,
these non-contact sensory devices come in two classes (1) absolute (2)
incremental. In former case, the encoder is able to give the actual linear or
rotational position even if power has just been applied to electro mechanical
system using the sensor. Thus a robot joint equipped with an absolute encoder
will not require any calibration cycle since the controller will immediately,
upon power-up, know the actual joint position.
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2 PROPOSED MODEL OF ROBOT VISION USING SMART CARD
TECHONOLOGY
2.1 OVERVIEW
After a study regarding the accidents in National Highways, it was found the
main cause behind these were due to over speeding of vehicles and change of lanes
during the course of travel. In addition to this we have introduced a chip card, which
will prevent the unauthorized usage of National Highways. In order to avert these we
have designed a paper, which would be valuable.
Ok
Fault
Strobe Lighting
Fig 2: Configuration of proposed model
ACCM: Automated Card Checking Machine
REGN.CHECK: Registration Number Check
SPEED CHECK: Done using Optical Encoders
Gray Scale Vision
Solid StateCamera
A C C M
Regn.
Check
Image
Check
SpeedCheck
(Encoders)
Information toControl Room
SafeTravel
Object
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2.2 PROCESSES INVOLVED:
2.2.1 SMART CARDS FOR TOLL COLLECTION:
Several states in India have a system of Tax called octroi which is tax
collected for goods or entry. This introduces a tremendous amount of paper
work and also lack of transparency. By usage of Automated Fare Collection
System (prepaid Smart Card) will assist in reducing paper work and also will
ensure complete transparency at the toll. A contact less Smart Card with
electronically pre-loaded money is used to pay the exact fare by flashing the
card to contact less Smart Card reader. The Card communicates with the
reader through Radio Frequency. This method gives a significant benefit to
the Highways Department.
The procedure is that the highway user should buy the Smart Card in
advance to his usage of the National Highway. The highway user is expected
to insert the Smart Card in the Automated Card checking System and if the
required conditions were satisfied, the user would be permitted to enter the
National Highway.
2.2.2 ROBOT VISION SYSTEM:
The Robotic Sensors have the capability of identifying the vehicle to a
distance of 50 meters on either side and accordingly the Robotic Sensors are
placed.
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2.2.3 IMAGE ACQUISITION AND DIGITIZATION:
Video Camera: CHARGE COUPLED DEVICE (SOLID STATE CAMERA)
Vision System: GRAY SCALE VISION SYSTEM
1. The basic idea of using a Gray Scale Vision System is to exactly get
the image of the vehicle and the Registration Number of the vehicle so as to becompared with the images already stored in the host computer.
2. If the Registration Number of the vehicle that is traced is not present
in the sorted list of Registration Numbers then this indicates an unauthorized
usage of the highway for which the highway user is to be fined.
Illumination: STROBE LIGHTING
In Strobe Lighting, a short pulse of high -intensity illuminates the scene
light, which causes a moving object to appear stationery. The pulse of light
can last 5-500 microseconds. This is sufficient time for camera to capture the
image although the camera actuation must be synchronized with that of the
strobe light.
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2.2.4 IMAGE PROCESSING AND ANALYSIS:
Thresholding:
Thresholding is one of the Segmentation techniques. This technique is
very useful in getting the image of the approaching vehicle with the
Registration Number in white or black.
2.2.5 INTERPRETATION:
Technique used: TEMPLATE MATCHING
The images of most commonly used models of vehicles are
stored in the host computer. The image of the approaching vehicle is
compared with the images in the host computer. And if the images of the
vehicle dont match, then it indicates the improper usage of lanes. Then
immediately the particulars about the vehicle are stored and informed
immediately to nearby Control Station.
SPEED CHECK:
The speed of the vehicles is calculated using the Velocity Sensors.
The velocity Sensor used in this system is Encoders.
Encoders:
Encoders are non-contact type position sensors. Unlike
potentiometers, which give analog signals, encoders give digital signals
directly. They basically consist of a photo transmitter (light source), photo
receiver (photo cell).
Types of Encoders:
1. Incremental Encoders:2. Absolute Encoders:
Rotary Absolute Encoder:
The absolute encoder is capable of giving the correct rotary position at
all times even after power-up has occurred. The device produces a separate
and unique coded word for each vehicle position and unlike the incremental
encoder; every reading is independent of the preceding one. A major
advantage of the absolute encoder is that even if system power is accidentallylost (due to a power outage or relay trip) for (e.g.) the device will remember
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where it is and will report this to the system as soon as power is restored.
Calibration of machines using this type of encoder is, therefore, maintained
even if the position of the rotating member is moved when the power is off.
Absolute Encoders consists of:
A multiple track light source
A multiple channel light receiver
A multiple track rotary disk
LANE CHECK:
Three basic components are:
Pre Processing (Image Pre Processing)
Initially the full image is converted into partial image and then edge
enhancement is performed and finally re-sampling is done. Edge enhancement
is basically a differentiation step, which provides robustness independent of
brightness variation due to the shadows of the moving sun.
Automatic Lane Detector
Lane Inference System
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ROBOTIC SENSOR SYSTEM FOR CHECKING UNAUTHORISED ENTRY
Host Computer(Control System)
way
card Card
Re n.No
Model
A C C M
Card
OPTICALENCODER
(speed
check)
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Flow Chart for Our
Robot Vision System
No
Yes
Yes
No
Yes
No
START
@ Is SmartCard Inserted
Vehicle allowed
* Is Cameraactivated?
Image Capture
Locate License Plate
Is there any
License Plate?
Identify Registration Number
**Check for
legal Usage
#SpeedCheck
##LaneCheck
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# Speed Check: ## Lane Check
No No
Yes Yes
* Usually the camera is expected to be activated always and placed at a quite
a far distance so as to provide the vehicle time to acquire a standard speed
@ If Smart Card is not inserted, the vehicle cant enter the Highway.
** The legal usage is checked is separated into 2 stages, both lane and speed
as to be appropriate, and it is given in two separate flow charts
# A separate flow chart has been given for speed check
## A separate flow chart has been given for lane check
$ For different vehicles different speed limits have been specified, and the
speed of the vehicle is found using rotary optical encoder and the speed is
compared with correct speed values. The vehicle is identified using template-matching techniques and then only speed is checked.
$$ For different vehicles different lanes have been allocated, and using
template matching techniques the vehicles image is compared.
Vehicle SpeedNoted
$ IsConditionsatisfied?
Safe Travel
Vehicles Lane
Noted
$$ Is Vehiclein Proper
Lane?
Safe Travel
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ADVANTAGES OF OUR PROPOSED SYSTEM:
ADVANTAGES OF VISION SYSTEM:
1. In current scenario, a system exists in United States of America,that identifies the over speeding vehicles and automatically spikes
appears within a certain distance both in front and at back of the
vehicle, which may lead to traffic jam in the Highway till officials
from the Control Station comes and clears it, and it also causes
damage to the vehicle.
But in Robot Vision System, no damage is caused to vehicle but itidentifies the vehicle uniquely using the Registration Number and
they are ultimately fined.
2. When accidents occur in National Highways, the clear picture ofthe Accident can be got, and the culprit can be held with then help
of Registration Number.
3. Unauthorized use of National Highway could be averted.
ADVATANGES OF AUTOMATED FARE COLLECTION SYSTEM
(Using SMART CARD)
1. This improves the operational efficiency.2. Minimization of Revenue leakage.3. Increased Cash flow due to advance collection.4. Highway user gets better service.
CONCLUSION
This system if implemented in National Highways would be very helpful in
reducing the number of accidents. In future this system would be forced to be
implemented as the usage of vehicles is on a constant increase. So we recommend this
paper to the Highways Department. The modified version of system can also be
introduced in the Railways, as it will be useful in averting the collusions between thetrains due to improper signaling.
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REFERENCES
Robotics by William P Groover.Robotic EngineeringAn Integrated Approach by Richard D Klafter
Thomas A Chmielewski
Michael Negin
Robotics and Automation Engineering by S.R. Deb
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