A New Algorithm for Vehicle Recognition

As the basic function of advanced assisted driving technology or autonomous driving technology, vehicle recognition plays an important role in lane change, collision avoidance and other applications. The current vehicle recognition method has the problem of slow recognition speed and false detection caused by camera movement. In order to solve this problem, this paper improves the existing three-frame difference method. The candidate frames obtained by the three-frame difference method are then screened and identified by FAST feature extraction, and tested in a typical vehicle video data set. The test results show that the average number of targets detected by mistake per frame is reduced from 1.5 to 0.15 when the camera is rotating incorrectly, and the detection rate is also increased by 10% when the camera is not moving.