automatic license plate recognition system for indian vehicle identification (paper id 17)

By:-

Kuntal Bhowmick, Subhojit Roy, Deepak Kumar Jha1

Contents Introduction The Architecture Workflow Steps for License Plate Detection Image Plate Pre-Processing Edge Detection-By SOBEL Operator Experimental Results Future Works Reference

Automatic License Plate Recognition System For Indian Vehicle Identification

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IntroductionAutomatic License Plate Recognition System For Indian Vehicle Identification

What is ANPR?

Automatic Number Plate Recognition (ANPR) is a practical application

of image processing which uses number (license) plate is used to

identify the vehicle.

Applications

Identification of stolen cars.Smuggling of Cars.Invalid license plates.Usage of cars in terrorist attacks/illegal activities.Applications in traffic systems (highway electronic toll collection, red light violation enforcement, border and customs checkpoints, etc.).

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Introduction continued… A vehicle registration plate is a metal or plastic plate attached

to a motor vehicle or a trailer for Official Identification purposes.

The registration number is a numeric or an alphanumeric code that uniquely identifies the vehicle within the issuing region’s database.

ANPR Cameras are specialized types of CCTV camera that has software built into it to help ID and capture license plates on still and moving vehicles.


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The ArchitectureAutomatic License Plate Recognition System For Indian Vehicle Identification

Input image

The approach do handles the entire ANPR module addressing each of the steps but the novelty lies in the segmentation scheme adopted.

Sofware part

Pre-Processor Analyzer

Recognizer

Segmentation Unit

OutputPercentageAccuracy

Software part

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Workflow

Images of Rear License plate is taken from real environment .

Pre-Process Digital Images of License Plates by Grey-scale conversion, Noise Reduction and Contrast enhancement using histogram equalization.

Application of the proposed method for localization/segmentation of the license plate.


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Steps for License Plate Detection

Step 1:-Collection of different Vehicle’s Image.

Step 2:- RGB to Grey Scale Image Conversion.

Step 3:- Edge detection of the processed image.

Step 4:- Area detection of Number Plate.

Step 5: Segmentation of the plate.


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Image Plate Pre-ProcessingAutomatic License Plate Recognition System For Indian Vehicle Identification

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Edge Detection-By SOBEL Operator The Sobel operator is one of most commonly used edge

detectors. The Sobel edge detector uses a pair of 3x3 convolution

matrices. The first is dedicated for evaluation of vertical edges, and

the second for evaluation of horizontal edges.


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Applying the Sobel operator- Examples


All edges in the image have been detected and can be nicely separated from the background using a threshold of 220.

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11 Edge Detection-By SOBEL Operator

Grey Scale image after image enhancing.

After applying Sobel edge detection method.

12 Removing Lower Connected Componets

After edge detection removes all connected components that have lower than p(eight pixel in our method) pixels. Thus it will produce another binary image.

Steps:-1. Determine the connected components. L= bwlabeln(BW,conn);

2. Compute the area of each component. S= regionprops(L,‟Area‟);

3. Remove small objects Bw2 = ismember(L,find([S.Area] >= p));

13 Filling the Holes

The set of background pixels are known as hole that cannot be reached by filling the background from the edge of the image.

The holes in the binarized image are filled.

14 Lower Components Removal

Image after removing components with connectivity less than 1200 pixel.

15 Lower Components Removal… Continued

Using Matlab toolbox function bwareaopen() that specifies the desired connectivity.

All components connectivity lower than 1200 pixel are removed to get the actual location of the number plate.

16 Final Positioning and Cropping

We output the four vertexes coordinates of the last selected region after morphological filtering and extract the number plate.

The final positioning of the number plate after cropping.

17 Experimental ResultsWe have run our proposed method on desktop computer with Core2 due processor 2.26 MHz with 2 GB of RAM under MATLAB 7.14.0.739 R2012a 32-bit(win32) environment. Several vehicle images are captured using 3.2 mega pixel camera as well as 13 mega pixel cameras. In the experiments, we test our proposed method on the different type car image to identify the location accurately.

Future Works

Recognition of Segmented Character.

Working with rotated Number Plates.

Adding some new features to the algorithm.


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References1. “Matlab Documentation Website,”. [Online]. Available:

http://www.mathworks.in/help/vision/.

2. Thota Sridevi, Chilukuri Sindhu, Pendyala Naga Praveen Kumar,Perupogu.Sagar, “Morphology based Number Plate Local ization for Vehicular Surveillance System”, IJMER, vol.2, issue.2, 2012, pp 334 -337.

3. Feng Yang, Zheng Ma “Vehicle License Plate location Based on Histogramming and Mathematical Morphology “, 2005.

4. Park, S. H., Kim, K. I., Jung, K., and Kim, H. J., (2009), “Locating ca r license plates using neural network,” IEE Electronics Letters, .35, 17, pp. 1475-1477.

5. CheokMan, Kengchung “A High Accurate Macau License Plate Recognition System”, 2008

6. R. C. Gonzalez, and R. E. Woods and S.I.Eddins Digital Image Processing using MATLAB.Pearson Education, 2008


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http://www.mathworks.in/help/vision/


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automatic license plate recognition system for indian vehicle identification (paper id 17)

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