The Research Of Car License Plate Recognition Technology Based On Neural Network

In the modern Intelligent Transportation System(ITS), License Plate Recognition(LPR) is one of the most critical technologies and it can be broadly applied in car management at gate, electronic toll collection system, traffic flow control, stolen vehicle inquiry and so on. Compared with traditional vehicles management methods, it greatly improves managing efficiency and level, and saves manpower and material resources, realizes vehicle management standardized and scientific, has attracted more and more attention by people, and has a very broad application.Generally LPR system consists of three parts, those are license plate location, character segmentation and character recognition. Based on image procession technology and artificial neural network technology, the paper researches and analyses the license plate location, the image pretreatment, character segmentation, feature extraction and character recognition process of the car license plate character recognition and has carried on simulation in the environment of MATLAB. Firstly, in the location process, adopts a license plate technology based on color character and the frequency of gray change. The paper has realized the thick location of the license plate by using the S value of the blue color is bigger in the blue bottom and white word license plate. Then, according to the character of license plate image's frequency of gray change, the paper has realize the accurate location of the license plate.Secondly, in the part of image preprocess, the paper has enhanced image contrast by stretching the gray of image, used Ostu method to change greysacle image into binary image.Thirdly, in the part of character segmentation, based on the gray change property and vertical projection threshold, the paper has used a method to eliminate the borders of plate image. Segments characters of license plate by vertical projection and combining with the priori knowledge of plate.Finally, aiming at four kinds of different recognition problems of Chinese character, the letter, letter of figure,figure, the paper has designed four kinds of different classification devices to recognize them by using the improved BP neural network. Experiment results show that the method this paper presents has some advantage such as accurate location, high recognition rate. LPR is a comprehensive research item, which involves digital image processing and pattern recognition, and is far-reaching significance in theory and application.