Research Of License Plate Recognition And Vehicle Detection For Intelligent Transport Systems

Traffic information acquisition and processing is the key to urban intelligentized transportation, and has wide applications in transportation planning and transportation manage control utilities. This paper is aimed at traffic parameter detection by means of digital image processing technology.Traffic parameter detection which based on image recognition technology acquires vehicle model, vehicle speed, vehicle license plate etc. Many parameters are very important in wide application of Intelligent Transport Systems. In this paper, we only study vehicle license plate recognition and vehicle model detection of traffic information detection system.In vehicle license plate recognition aspect, the position of vehicle license plate is obtained by means of edge detection and characteristics of scan line. Moreover, we introduce Da-Jin method, Radon transformation, erode and dilate operation to obtain the precise position of vehicle license plate and use vertical projection to segment license plate characters. We choose the feature of rough grid as the feature of characters recognition, and directly input the improved unified characters primitive feature to BP neural network classifier to recognize the license plate characters.In vehicle model detection aspect, a new vehicle detection system is designed using algorithms for fast adaptive background extraction, update and background subtraction with contour track to improve the precision of vehicle localization. The vehicle characteristic data are extracted by using binary algorithm, edge detection algorithm, erode and dilate operation, and then the vehicles can be classified by means of D-S evidence theory. Experimentation shows that the method is reliable and efficient.In this paper, we mainly discuss the structures, functions, design and implementation of vehicle license plate and vehicle model recognition system.