一种夜晚道路环境下的后方车辆检测方法

A Method for Rear Vehicle Detection in Nighttime Road Environment

目前,基于视觉传感器的车辆检测已经成为车辆驾驶辅助领域的研究热点。但是迄今为止,大多数研究集中在白天好的光照条件,对夜晚条件下的车辆检测研究较少。本文提出了一种基于车灯的夜晚道路环境下的车辆检测算法,利用摄像机采集实时图像来检测自车后方的车辆。首先,基于亮度信息提取夜晚环境图像中的光亮目标物,然后,对提取的光亮目标物进行验证,去除路灯等干扰光源,从而得到真正的车辆头灯;最后,按照基于知识的方法,对提取到的车灯进行组合,并对组合后的车灯对进行验证,从而检测出夜晚道路环境下的车辆。实验结果表明本文算法易于实现,识别率高,适应性好。

Recently, vision sensor based vehicle detection becomes an attractive research area for the driver assistance system （DAS）. But most research was carried out in the day time with a good lighting condition and what little research so far done in the night time assumed no interference of light. Hence a headlights based vehicle detection algorithm at nighttime environment is proposed in this paper. The proposed algorithm detects the rear vehicles via real-time image sequence capture. Firstly, bright objects are extracted from the nighttime road scene images. Then the extracted bright objects are verified based on rules to eliminate the interferential light sources and obtain the actual vehicle headlights. Finally, a knowledge-based method is used to cluster vehicle headlights. The clustered headlights are then validated. Experimental results demonstrate the feasibility, effectiveness and robustness of the proposed algorithm on vehicle detection at night.