Research Of Video Vehicles Detection And Early Warning Algorithm And Its Implementation On DSP

In recent years, with the development of the traffic and the increasing number of vehicles, traffic safety accidents increase frequently. Defensive driving has become an increasingly prominent problem. Intelligent Transportation Systems (ITS) and the Driver Assistance Systems (DAS) have become a hot research topic at home and abroad. Real-time detection technology of the vehicles at the front is one of critical content belonging to Driver Assistance Systems. It has very important significance to realize the parking assistance and collision avoidance.This thesis has designed a moving and stationary vehicles detection algorithm for real-time image and developed a real-time vehilces distance early warning system. The algorithm has utilized vehicles plate features, texture features, gray symmetry features and statistical characteristics. It is programmed on DSP in the end.In the aspect of algorithm research, firstly use the clustering of blue and yellow plate which is the most common in the actual life in YUV color space to extract the plate and process the binary image by corrosion expansion, connected component labeling, to realize the initial location of the vehicles area. Then use the symmetry texture features and gray preliminary to exclude non-vehicles. Besides, structuring local feature subspace of the vehicles, it can solve the problem of vehicle obscured effectively, and then use Two-Dimensional Principal Pomponent Analysis (2DPCA) and the minimum distance classifier vehicles verification to realize the final vehicles detection and localization. Finally, a vehicles distance early warning module is established and it is combined with the vehicles detection algorithm to alarm when the vehicles detected is very close, and determines vehicles warned left and right orientation.This thesis has completed video vehicles detection algorithm and simulation tests in the MATLAB platform firstly. In terms of hardware implementation, firstly, the thesis analyzes the hardware requirements, and selects ICETEK-DM6437-B evaluation as a hardware platform and selects the CCD camera as a video capture tool. Secondly, at the stage of extracting plate area and locating the vehicles, the thesis uses the method of down-sampling the image to reduce the amount of data processed by the DSP, and the efficiency of detection system is significantly improved. Finally, the algorithm is completed in CCS integrated development environment, using the C language to realize the vehicles detection and vehicles distance early warning real-time.Experimental results show that the video vehicles detection and warning system designed has an above 90% accuracy rate, with a considerable robustness and practicality. The efficiency of optimized code has been significantly improved to process almost three frames per second, which is capable to meet the basic real-time requirements. Besides, the algorithm can effectively detect the vehicles which are obscured partly, reducing the influence of light and other external conditions.