Abstract Smnr

7/29/2019 Abstract Smnr

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LICENSE PLATE

RECOGNITION SYSTEMProject done by:

M. RESHMA ROOP - 09C21A0438M. HEMANTH KUMAR - 09C21A0442

V. BABU LOKESH - 09C21A0458

GUIDED BYMr. E.KRISHNA HARIASSOCIATE PROFESSOR, DEPT OF ECE


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CONTENTS :AbstractIntroduction

Objectives

Existing technology

Proposed systemBlock diagram

Software tools

Advantages

ApplicationsConclusions

References


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ABSTRACT:

Due to a huge number of vehicles, moderncities need to establish effectivelyautomatic systems for traffic managementand scheduling.

One of the most useful systems is-THEVEHICLE LICENSE-PLATE (VLP)RECOGNITION SYSTEM, which capturesimages of vehicles and read these platesregistration numbers automatically.


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INTRODUCTION

License plate recognition technology is an important part of

the vehicle detection system.

It plays an important role in intelligent transportation system.

For license plate positioning and obtaining the car license

character information, we are using fuzzy theory.

The BP neural network used to recognize the characters of

the license plate.


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Our system consists of three mainmodules:

a. VLP detection,

b. VLP segmentation,

c. VLP recognition.

In VLP detection, we propose an efficientboundary line-based method.

In VLP segmentation, we use

horizontal and vertical projection toseparate plate numbers.

In VLP recognition, each plate number willbe recognized by OCR module.


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EXISTING TECHNOLOGY:

This paper presents a method which

applies fuzzy theory.

To obtain the license information, we use

an improved BP neural networkalgorithm.


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Our system, consists of fourmodules:

Pre-processing,

VLP detection, Character segmentation,

Optical character recognition(OCR),

in which the last three modules dealwith three main problems of a VLPrecognition domain.


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BLOCK DIAGRAM:

Images taken

from Camera

License-plate

characters

Preprocessing VLP Detection

SegmentationOCR


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SOFTWARE TOOLS:

Motorola Droid Phone:

Great for snapping a quickpicture.

Originally thought RGB

values could be exporteddirectly.

MATLAB:

One of the best, fastest

mathematical analysis tools.

Many built-in image

processing functions.


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ADVANTAGES:

Recognition systems has beenimproved.

Reduce the complexity.

Accuracy is more.

High convergence speed.


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APPLICATIONS:

It is very useful for many traffic managementsystems.

It is also used in real-time systems.

It enhance the system robustness.

It is an effective boundary line based method.


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CONCLUSIONS:

The system performs well on various types of VLP

images, even on scratched, scaled plate images.

In addition, it can deal with the cases of multiple

plates in the same image, or different types of vehicles

such as motorbike plates, car plates or truck plates.

However, it still has a few errors when dealing with bad

quality plates.


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REFERENCES:i. D.A.Duc,T.L.Du,T.D.Duan,The 7th International

Conference on Electronics, Information, andCommunications,pg438-441,Vol~1,2004.

ii. A. Rahman, Ahmad Radmanesh, A Real Time

Vehicles License Plate Recognition,

Proceedings of the IEEE on Advanced Videoand Signal Based Surveillance,2003.

iii. Jun-Wei Hsieh,Yung-Sheng Chen,License

Plate Detection from Complex Scenes, 16thInternational Conference,Vol~3,2002.


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Thank you

for yourattention...

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Abstract Smnr