Architectural Model of Robot Vision System Smart Card Technology

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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Documents

Architectural Model of Robot Vision System Smart Card Technology