Research On Key Technologies Of Information Processing In Intelligent Transportation System

Intelligent Transportation System or ITS, is an transportation management system which integrates advanced information technology, data communication technology, electronic sensing technology, computer technology and all kinds of other advanced technologies synthetically and applies them to the whole ground traffic management system. ITS constructs an effective in large-scale, real time, exact, and efficient transportation system, and it has become an important development aspect of the modernized transportation system in the 21st century. The main work of the thesis is research on some key technologies of information processing in ITS, which includes: vehicle license character recognition algorithm, vehicle localization algorithm, virtual-line based video vehicle detection algorithm and video transportation detection system design method.The innovations of the thesis are embodied in four aspects as follows:1) A vehicle license character recognition algorithm based on pulse coupled neural network (PCNN) is proposed. It firstly applies PCNN in vehicle license character recognition. Based on simplified PCNN model, it extracts three different image features and utilizes them to recognize number, letter and Chinese characters. Compared with common algorithms based on BP neural network,this algorithm has advantages of higher total recognition rate, better fault tolerability and stability, stronger robustness, and is more convenient and flexible to use. Its recognition speed is fast enough to satisfy the demand on speed in applications.2) A contour projection vehicle localization algorithm based on phase information is proposed. It combines the information of the image in HSV color space and RGB color space, detects contour of vehicles based on phase congruency utilizing log Gabor wavelet filters, then uses projection method and vehicle area distinguishing algorithm to localize vehicles. Compared with common algorithms, it suffers smaller from the luminance, contrast of image, noise and shadows, and has higher accuracy. It is also suitable for images including more than one vehicle. 3) An improved virtual-line based video vehicle detection algorithm is proposed. It introduces two-level detection, utilizing luminance information and the chrominance information respectively. The improved algorithm can effectively increase the accuracy of old one and reduce the FRR and FAR. It can satisfy the request of real-time performance.4) A design of dual-cored embedded video vehicular detection system based on ARM processor and DSP is proposed. The method of hardware connection between two units and the driver program of the interface are introduced. The design methods of operating system and application programs are also presented. This system combines 32 bit embedded microprocessor ARM and digital signal processor DSP, and it sufficiently embodies the superiority of dual microprocessor system. Compared with common video vehicular detection systems,it has advantages of small volume, low cost, low power consumption, good stability and expandability, facility of operation and friendly interface. It can satisfy the demand on real-time.