Motion Vehicle Recognition and Tracking in the Complex Environment

Abstract

Moving vehicle recognition and tracking is the key technology in the intelligent traffic monitoring system. For the shortcomings and deficiencies of the frame-subtraction method, a binary discrete wavelet transforms based moving object recognition algorithm is put forward, which directly detects moving vehicles in the binary discrete wavelet transforms domain. For the shortages of RGB or HSV color space based vehicle shadow segmentation algorithms, shadow segmentation algorithm based on YCbCr color space is proposed. First, the motion area which includes the vehicle and the shadow is selected by binary discrete wavelet transforms, and then the original data of the shadow according to the characteristics of the occurrence of shadow is chose, finally, the shape and location of the vehicle region is determined. An automatic particle filtering algorithm is used to track the vehicle after recognition and obtaining the center of the object. The actual road test shows that the algorithm can effectively remove the influence of pedestrians, cyclists in the complex environment, and can track the moving vehicle exactly. The algorithm with better robustness has a practical value in the field of intelligent traffic monitoring, and it is adopted by Tianjin Traffic Bureau.