基于车辆视觉的车道闸杆防撞系统研究

Research on lanes collision avoidance system of the brake lever based on vehicle vision

车道闸杆故障在收费站等地时有发生,为了解决这一问题,提出了一种基于车辆视觉的闸杆防撞系统的解决方案。该方案主要包括差值图像的自适应阈值提取、二值图像的中值滤波与开运算以及背景的分块实时更新,并在此基础上提出了一种基于背景差分的车辆检测方法。该方法有效解决了精确阈值提取困难与背景更新效果差等难题。实验验证了该系统的车道闸杆防撞功能,该系统具有运行速度快、稳定性高等特点。

Sometimes driveway gate-bar faults occur in places such as toll stations. In order to solve this problem , this paper presents a solution of lever collision avoidance system based on vehicle vision. The solution mainly includes the extraction of difference image′s adaptive threshold based on Otsu method, the median filtering and open operation on binary image, as well as the background block′s real-time update. Based on all above, it proposes a vehicle detection method based on background subtraction. This method effectively solves the challenges of the difficulty to precise threshold extraction and the poor effect of background update. The experimental results test and verify the driveway gates anti-collision function of the system. At the same time, the system can run fast with high stability.