一种基于计算机视觉的地铁站台异物检测算法

地铁已成为大型城市的主要交通工具，如何保障乘客的安全成为地铁运营的热点问题。文章在现有的车门与屏蔽门之间人工检测技术的基础上提出一种基于计算机视觉的空间异物检测算法。该算法通过对车尾处灯带的完整性进行检测，判断车门与屏蔽门间是否存在异物，进而辅助司机进行开车前的安全检查，保障列车的运行安全。实地采集视频数据进行实验分析，结果表明，文章所提方法可以准确检测出空隙中异物。

Foreign object detection algorithm for subway platform based on computer vision

Subway has become the main means of transport in large cities, and how to protect the safety of passengers has become a hot issue in subway operations. Based on manual detection between the door and platform screen doors (PSD), this article proposed a foreign object detection algorithm based on computer vision technology. The algorithm was used to detect the integrity of vehicle tail lamp belt, judge whether there was foreign objects between the door and the PSD, and then assist the driver to carry out safety inspection before driving, ensure the safe operation. Video data were collected on the spot for experimental analysis, and the results showed that the proposed method could accurately detect the foreign objects in the gap.