Vehicles Detection and Tracking Algorithm for Complex Nighttime Traffic Scene
SHEN Zhen-qian;MIAO Chang-yun;GENG Lei;The School of Electronics and Information Engineering,Tianjin Polytechnic University;
Vehicles detection and tracking algorithm for nighttime traffic surveillance is proposed in order to further improve the accuracy of video vehicle detection and tracking at night. Light spots segmentation and connect- component matching techniques are used to detect and locate headlights of vehicles and employs region tracking-based method to track headlights. Headlights, which are the only salient features of vehicles in nighttime, are segmented by improved Otsu method, and non-vehicle illumination sources are filtered out according to the geometrical shape, size and location of headlights. Then, headlights are paired and classified based on the geometrical symmetry of headlights. Finally, a region-based tracking algorithm is employed to locate and track headlights. The results prove that the average accuracy rate of the algorithm is more than 97%, and the processing speed is 15.8% higher than the existing methods.