An Approach To Recognition Technique Of License Plates In Complicated Context

License Plate Recognition is one important constituent part of the Intelligence Transportation System (ITS). Especially it is the license plate recognition in complicated contexts. It covers comprehensive application areas and enjoys a great application perspective. Its development is sure to accelerate the progress of ITS. In light of the weak points in contemporary license plate recognition algorithm, the present study focuses on the techniques of license plate recognition within complicated contexts.This thesis is divided into the following several aspects for the research: 1) the detection and location of the vehicle in complicated contexts. The present study employs the instantaneous difference method based on block, that is, to detect the vehicle by doing the block difference of the frame 3×3 with dots in the center for two successive images in the video array and then squaring the difference to strengthen the information of movement. The vehicle is accurately located with the help of techniques such as filter and dilation. The experiment has showed that this kind of algorithm holds sound testing effects. 2) license plate recognition. The first step is to make binary images of vehicles and to do a series of mathematic morphology operation. And then is to filter according to the existing information and to come up with the license plate areas for candidacy. After that, the color edge detection is made for the chosen license plate areas and license plates are accurately located according to fixed color-pair information and structural information in license plate areas. This kind of algorithm can reach the accurate location rate with a rather high degree as well as satisfy the real-time performance. 3) character segmentation of license plates. Because characters in the license plate areas are connected except for Chinese characters, the present study abstracts single characters by the way of combining information based on veins and connected domains. It is easy to do the algorithm, and to some extent, this can help eliminate the bad effect brought about by pretreatment as well as fundamentally solve the problem of slant license plates' segmentation. 4) character recognition of license plates. This part puts forward a new way of character recognition which is based on Null Space PCA and the improved BP neural network. At first, for the aim of dimension, the pretreated character images should be made to undergo the transfer of Null Space PCA. Then different characters should be put respectively into four different classifiers of neural network (they are Chinese characters, letters, letters and numbers, and numbers). The result of the experiment shows that this kind of algorithm can reach the high recognition rate and recognition speed, which can satisfy the demand of recognition in the real-time performance.The present study combines both theories and practice, and delves into the various key techniques in the license plate recognition system under complicated contexts. New ideas and methods are given, which has great research significance and adds to the value of application for the character recognition technique of license plates.