关键词: 车流量检测, 检测区域, 自适应背景差分, 阴影去除

Abstract: Video-based traffic flow detection systems are easily influenced by background changing and vehicle shadows. A method for traffic flow detection using self-adaptive background difference and shadow removing is proposed. First, the adaptive background model is constructed and used to extract image background; and then interested vehicles are detected from video candidate area by self-adaptive background difference. Changes the difference image into binary image by given thresholding, and fill the holes within the extracted objects using morphological reconstruction by erosion. Second, according the fact that the gray value of the shadow area is less than that of the vehicle area, sweep the binary image object along the direction from shadow area to vehicles area, and compare the conjoint pixel gray value of the original gray image in the same position. By this way, most vehicle shadows can be removed. Simulations show that this method can efficiently detect the highway traffic flow and is less influenced by vehicle shadows and background changing.

Key words: vehicle flow detection, candidate area, self-adaptive background difference, shadow removing