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DCT vs. DWT Based License Plate Detection

Amr E. Rashed


Automatic license plate recognition (ALPR) is one of the most important aspects of applying computer vision techniques and image processing algorithms toward intelligent transportation order to recognize a license plate efficiently; first license plate must be detected or located from a vehicle image. This step is considered to be the most crucial step of an ALPR system, which affect the recognition rate and speed of the system also. In this paper, two techniques are proposed one based on DCT features and the other is based on DWT features with some different neural network classifiers such as multilayer perceptron (MLP), modular neural network, and generalized feed forward neural network .in this method, firstly histogram equalization technique is used to increase contrast secondly vertical and horizontal edge detection are applied to help in removing border and background then image segmentation and ANN classifiers takes place .proposed techniques are explained and designed using Matlab. We achieved about 99.8% detection rate for small dataset with mean square error about 0.0063.


license plate detection (LPD), license plate segmentation, discrete cosines transform (DCT), Support

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