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License Plate Recognition System
 

License Plate Recognition System

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Abstract: ...

Abstract:
With an everyday increase in the number of cars on our roads and highways, we are facing numerous problems, for example:
• Smuggling of cars
• Invalid license plates
• Identification of stolen cars
• Usage of cars in terrorist attacks/illegal activities
In order to address the above issues, we took up the project of developing a prototype, which can perform license plate recognition (LPR). This project, as the name signifies, deals with reading, storing and comparing the license plate numbers retrieved from snapshots of cars to ensure safety in the country and ultimately help to reduce unauthorized vehicles access and crime.
License Plate Recognition (LPR) has been a practical technique in the past decades. It is one of the most important applications for Computer Vision, Patter Recognition and Image Processing in the field of Intelligent Transportation Systems (ITS).
Generally, the LPR system is divided into three steps, license plate locating, license plate character segmentation and license plate recognition. This project discusses a complete license plate recognition system with special emphasis on the Localization Module.In this study, the proposed algorithm is based on extraction of plate region using morphological operations and shape detection algorithms. Segmentation of plate made use of horizontal and vertical smearing and line detection algorithms. Lastly, template matching algorithms were used for character recognition.
The implementation of the project was done in the platforms of Matlab and OpenCV.

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  • Full Name Full Name Comment goes here.
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  • you can download code this here
    https://www.youtube.com/watch?v=5ZmdtKzlNbA
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  • please, could you send the matlab and opencv codes??
    my mail ngocquan12a2@gmail.com
    Thanks!!!!
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  • please, could you send the matlab and opencv codes??
    my mail soha.samy2010@gmail.com
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  • Do you share it? Is it possible to use? Is it possible lo localize ?
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  • I want to get a matlab code.
    My mail is : ayoub.karine@gmail.com
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    License Plate Recognition System License Plate Recognition System Presentation Transcript

    • LICENSE PLATE RECOGNITION SYSTEM USING MATLAB AND OPENCV Group Members Asiya Zafar Iqra Farhat Hira Batool Rizvi Project Supervisor Dr. Fawad Ahmed Department of Electrical Engineering HITEC University Taxila Cantt.
    • BASIC MOTIVATION With an everyday increase in the number of cars on our roads and highways, we are facing numerous problems, for example:  Identification of stolen cars  Smuggling of Cars  Invalid license plates  Usage of cars in terrorist attacks/illegal activities 2
    • AIM To address these issues, we intend to develop a prototype system in MATLAB and OpenCV which can perform license plate recognition (LPR). 3
    • WORKFLOW  Process Digital Images of existing/modified algorithms. License Plates using  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 and 4 OpenCV is also used for localization.
    • BASIC MODULES OF THE SYSTEM  License Plate Localization Locating the license plate in an image.  Character Segmentation Locates the alpha numeric characters on a license plate.  Optical Character Recognition (OCR) Translates the segmented characters into text entries. 5
    • Block Diagram 6
    • Start Localization Characters And Numbers Segmentation Feature Extraction Of Segmented Image Recognize The Extracted Features Show The License Plate End 7
    • LICENSE PLATE LOCALIZATION Edge Detection Morphological Operations Extracting The Plate Region 8
    • Flow Chart of Localization in Matlab 9
    • Start Load Image From File Convert Image Into Grayscale Filter To Detect Edges In The Image Morphological Operations Are Applied On The Image Find The Connected Objects In The Image Determine The Rectangle In The Connected Objects Compare The Size With The Threshold Value Determine the Coordinates Of Rectangle Using Coordinate Geometry Retrieve The Rectangle From The Image Using The Respective Coordinates Show The License Plate End 10
    • LOAD THE IMAGE FROM FILE Img=imread(‘filename’) 11
    • CROPPING AN IMAGE img=imcrop (img,[ymins ymins Wnew Hnew]) 12
    • CHANGING THE TYPE f1=rgb2gray(img); 13
    • EDGE DETECTION f2=edge(f1,'sobel'); 14
    • MORPHOLOGICAL OPERATIONS se=strel('rectangle',[15 17]); se=strel(‘disk',20); img=imfill(img,'holes'); img=imdilate(img,se); d1-imopen(img,se); 15
    • EXTRACTING PLATE REGION Labeling and detecting the rectangle with the set threshold, the threshold was determined by the distance between the car and the camera. LP=imcrop(lp1,[xmin ymin ow oh]) 16
    • CHARACTERS SEGMENTATION Preprocessing Horizontal And Vertical Segmentation 17
    • PREPROCESSING Preprocessing is very important for the good performance of character segmentation. Preprocessing consists of :  Determination of the image type.  Mode conversion.  Clearing objects less than a threshold value. 18
    • 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. 19
    • CHARACTERS RECOGNITION Template Matching Template matching is one of the most common and easy classification method for recognizing the characters. 20
    • TEMPLATE MATCHING The used templates are given in the figure below: 21
    • CONTI…. Correlation is used to match the image from the license plate and the template’s image. The following figure shows the numbers in a text files. 22
    • EXPERIMENTAL RESULTS 23
    • 24
    • WHY CHOSE OPENCV FOR PROJECT  To move to a Real Time Environment.  The problem of manual editing of Localization was even fixed in OpenCV and it worked well for cars at varying distances. 25
    • WHAT IS OPENCV  OpenCV is an open source computer vision library.  It is a collection of C functions and a few C++ classes that can be used to implement some popular Image Processing and Computer Vision algorithms.  OpenCV has cross-platform means It can implemented on multiple computer platforms.  It runs on Windows and Linux. Its mainly focuses towards real-time image processing. 26
    • Flow Chart of Localization in OpenCV 27
    • Start Load Image From File Convert Image Into Grayscale Convert Image Into Binary Image Filter To Detect Edges In The Image Morphological Operations Are Applied On The Image Find The Contours In The Image Detect The Rectangle In The Image Retrieve The Rectangle From The Image Using The Respective Coordinates Show The License Plate Image 28 End
    • LOAD THE IMAGE FROM FILE img=cvLoadImage (fileName); 29
    • CONVERT THE IMAGE INTO GRAYSCALE IMAGE cvCvtColor( src,dst, CV_RGB2GRAY ); 30
    • CONVERT THE IMAGE INTO BINARY IMAGE cvThreshold(src, dst, threshold, maxValue, CV_THRESH_BINARY); 31
    • EDGE DETECTION cvCanny( binaryImage ,edgImage,50, 255,3) . 32
    • MORPHOLOGICAL OPERATIONS cvDilate( edgImage ,dImage,NULL,1); 33
    • FIND THE CONTOUR IN THE IMAGE  cvFindContours(dImage, storage1, &contour, sizeof(CvCont our), mode, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0)); cvDrawContours(contourImg, contour, CV_RGB(255,255,255), CV_RGB(0, 0, 0),2,2, 8,cvPoint(0,0));  cvDrawContours(contourImg, contour, CV_RGB(255,255,25 5), CV_RGB(0, 0, 0),2,CV_FILLED, 8,cvPoint(0,0)); 34
    • DETECT RECTANGLE drawSquares( img, findSquares4( img, storage ) ); 35
    • EXTRACTING PLATE REGION 36
    • RESULTS 37
    • PROBLEMS WITH THE MATLAB SYSTEM The problems that we faced during Localization were:  Issues of time management  Manual Changes in the code every time there is a change in the orientation of the camera 38
    • PROBLEMS WITH THE OPENCV SYSTEM The problem that we faced during Localization was  On some Cars the morphological operations used in this algorithm are insufficient to remove noise therefore it is difficult to extract the license plate. 39
    • 40