The document outlines a MATLAB-based vehicle number plate identification system utilizing optical character recognition (OCR) for applications such as smart parking management and stolen vehicle identification. It details the system requirements, literature review of relevant papers, and describes modules involved in image processing, such as plate extraction and character segmentation. The study emphasizes the effectiveness of image processing techniques to enhance vehicle identification accuracy and presents a workflow for real-time database comparison.

1. MATLAB Based Vehicle Number Plate
Identification System using OCR
Submitted by
Ghanshyam Dusane (BE-A 46)
Guided by
Prof. Neeta Pingle
Marathwada Institute of Technology, Aurangabad
Department of Electronics and Communication
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2. Contents
 Need
 AIM
 Literature Survey
 OCR
 Block Diagram
 Flow Chart & Work Flow
 Basic Modules And Sensors
 Examples
 Applications
 Conclusion
 References 12/4/2015 7:53:54
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3. Need
Smart Parking System Management
Identification of stolen cars or bikes
 Smuggling of Cars or bikes
 Invalid license plates
 Usage of cars in terrorist attacks/illegal activities
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4. AIM
We intended to develop a system in MATLAB
which can perform detection as well as
recognition of Vehicle License Number plate
The objective of this project is to recognize
Vehicle License Number plate using serial
communication.
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5. SYSTEM REQUIREMENTS
Software Requirement Hardware Requirement
System Type: 32-bit operating
system,
x86 based processor
WEB- CAM
OS Installed: Windows XP or
higher
Personal Computer (PC)
MATLB 7.0 or Above installed Microcontroller
Servomotor/DC Motor
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6. Literature Review
 Paper 1
“AUTOMATIC NUMBER PLATE RECOGNITION SYSTEM FOR VEHICLE
IDENTIFICATION USING OPTICAL CHARACTER RECOGNITION”
Proceedings of the World Congress on Engineering and Computer Science 2012 Vol I WCECS
2012, October 24-26, 2012, San Francisco, USA.
Presented By :- MUHAMMAD TAHIR QADRI, MUHAMMAD ASIF
This paper presents a robust method of license plate detection and
recognition based on Hough lines using Hough transformation and template matching
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7.  Paper 2
“Automatic Vehicle Identification by Plate
Recognition”
World Academy of Science, Engineering and Technology International
Journal of Electrical Computer, Energetic, Electronic and Communication
Engineering Vol:1, No:9, 2007.
Presented By :- Serkan Ozbay, and Ergun Ercelebi
In this paper, a smart and simple algorithm is presented for vehicle’s license
plate recognition system. The proposed algorithm consists of three major parts:
Extraction of plate region, segmentation of characters and recognition of plate
characters. For extracting the plate region, edge detection algorithms and smearing
algorithms are used. In segmentation part, smearing algorithms, filtering and some
morphological algorithms are used.
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8.  Paper 3
“Automobile Number Plate Recognition And
Extraction Using Optical Character Recognition”
INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH
VOLUME 3, ISSUE 10, OCTOBER 2014
Presented By :- Raja Vikramdeep Singh, Navneet Randhawa
The purpose of this research is to develop an application which recognizes
license plates from vehicles. The system takes images of automobiles as input and
processes them. Once a license plate is detected, its digits are recognized and
displayed on the User Interface. This work focuses on the design of a single algorithm
used for extracting the license plate from a single image, isolating the characters of
the plate and identifying the individual characters
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9.  Paper 4
“A Review Paper on Automatic Number Plate Recognition
(ANPR) System”
International Journal of Innovative Research in Advanced
Engineering (IJIRAE)
Volume 1 Issue 1 (April 2014)
Presented By : - Dhiraj Y. Gaikwad and Pramod B. Borole
In this review paper, the automatic number plate recognition system
using vehicle license plate is presented. The system use image processing techniques
for identifying the vehicle from the database stored in the computer. The system works
satisfactorily for wide variation of conditions and different types of number plates. The
system is implemented and executed in Matlab and performance is tested on genuine
images.
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10. BASIC PROJECT
Input image ( from real
environment)
Algorithm using (MATLAB)
Output -Microcontroller serial
interfacing with hardware.
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11. Block Diagram
Vehicle WEB-CAM
OUTPUT-ASSCII Character
Character Recognition
Image Acquisition
Localization of Number Plate
Plate Segmentation
Door Control Microcontroller
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OCR System

12. OCR
OCR is a technology that enables
you to convert different types of
documents captured by a digital
camera into editable and
searchable data.
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Fig. OCR Technology

13. Flow Chart of extraction in
MATLAB
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14. 12/4/2015 7:53:54
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Start
Input Image
Pre-processing
Localization
Is Number
plate
detected?
OCR
Is vehicle
Number
recognized?
Message
Displayed
NO
NO
Comparing with
Database
Yes
Yes

15. WORKFLOW
 Image was taken from real environment .
 Process Digital Images of License Plates using existing/modified
algorithms.
 Algorithms will perform alpha numeric conversions on the captured license
plate images into text entries.
 System would check the extracted entries against a database in real time.
 The entire system is implemented in MATLAB is used for detection and
recognition .
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16. 12/4/2015 7:53:54
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Capture
image
Sensor
Digital
camera
Find plate
region
Plate
extraction
Database
segmentationRecognition
Image
processing
Register
Activates the
camera
Compare in order
to recognize
Detect the vehicle
Administrato
r
Use Case Diagram

17. Basic Modules of the System
 Detection is done by Character Segmentation
Locates the alpha numeric characters on a license
plate.
 Optical Character Recognition (OCR)
Translates the segmented characters into text
entries.
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18. Load The Image From File
 a=imread(‘car 10.JPG’)
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19. Preprocessing
Preprocessing is very important for the good
performance of character segmentation.
Preprocessing consists of :
Resizing image
Rgb to gray
Noise removal 12/4/2015 7:53:54
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20. Changing the TYPE
 c=rgb2gray(b);
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21. Extracting Plate Region
It is result of dilation after
noise removal .
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22. Edge enhancement
gdiff=imsubtract(d,e);
where ‘d’ is dilated and ‘e’ is eroded
image
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23. Morphological Operations
Morphological Operations
Thinning ( for character
isolation)
Finding connected
components of area more
than 200 pixels
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24. Characters Segmentation
Horizontal & Vertical Segmentation
Detect the horizontal lines in the image with a pixel value of
zero.
Converting the image into binary.
Use simple “for loops” to detect the portions of the image that
had connected objects with a pixel value of ‘0’ and hence
accordingly, the image was read.
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25. Characters Segmentation
Preprocessing Horizontal And
Vertical Segmentation
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26. Template Matching
Template matching is one of the most
common and easy classification method
for recognizing the characters.
We used code for OCR
Characters Recognition
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27. Applications
Red Light Violation Enforcement
Border And Customs Checkpoints
Smart Parking System Management
Detection Of Invalid License Plates
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28. Conclusion
The automatic number plate recognition system using
vehicle license plate is presented. The system use image
processing techniques for identifying the vehicle from the
database stored in the computer.
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29. References
 Optical Character Recognition
Ravina Mithe, Supriya Indalkar, Nilam Divekar 2013
International Journal Of Recent Technology And Engineering (Ijrte)
 Design Of An Optical Character Recognition System For Camera-Based Handheld Devices
Ayatullah Faruk Mollah, Nabamita Majumder Subhadip Basu, And Mita Nasipuri
2011 International Journal Of Computer Science Issues
 Number Plate Recognition Using an Improved Segmentation
Mr. G. T. Sutar , Prof. Mr. A.V. Shah P.G. Student, Department of Electronics Engineering, D.K.T.
Engineering College, Ichalkaranji, Maharashtra, India Associate Professor,
Department of Electronics Engineering, D.K.T. Engineering College, Ichalkaranji, Maharashtra
 A Review Paper on Automatic Number Plate Recognition (ANPR) System
International Journal of Innovative Research in Advanced Engineering (IJIRAE)
Volume 1 Issue 1 (April 2014)
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30. Any Queries ?
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31. THANK YOU !
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