This paper presents an effective vehicle and motorcycle detection system in the blind spot area in the daytime and nighttime\r\nscenes. The proposed method identifies vehicle and motorcycle by detecting the shadow and the edge features in the daytime,\r\nand the vehicle and motorcycle could be detected through locating the headlights at nighttime. First, shadow segmentation is\r\nperformed to briefly locate the position of the vehicle. Then, the vertical and horizontal edges are utilized to verify the existence\r\nof the vehicle. After that, tracking procedure is operated to track the same vehicle in the consecutive frames. Finally, the driving\r\nbehavior is judged by the trajectory. Second, the lamps in the nighttime are extracted based on automatic histogram thresholding,\r\nand are verified by spatial and temporal features to against the reflection of the pavement. The proposed real-time vision-based\r\nBlind Spot Safety-Assistance System has implemented and evaluated on a TI DM6437 platformto performthe vehicle detection on\r\nreal highway, expressways, and urban roadways, and works well on sunny, cloudy, and rainy conditions in daytime and night time.\r\nExperimental results demonstrate that the proposed vehicle detection approach is effective and feasible in various environments.
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