基于计算机视觉的地铁测速技术实现

Realization of Subway Speed Measurement Technology Based on Computer Vision

针对目前轨道交通市场上的一些以人工智能为主的地铁车辆列检产品在车辆变速时检测精度不高的问题,提出一种基于计算机视觉的地铁测速方法。首先,通过图像透视变换获取校正后的地铁图像,在校正后的图像基础上,利用深度学习目标检测方法定位车身区域。其次,对相邻两帧图像定位到的车身区域进行特征点检测,并采用区域最强特征点匹配方法获取匹配点对。然后,根据匹配点对计算出地铁移动的平均像素距离,结合像素尺寸换算出实际移动距离,再通过已知的相邻两帧图像时间差即可获取当前地铁实时速度。最后,根据实时检测的速度信息实时调整线扫相机行频,尽可能减少地铁车辆变速或者停车时产生的图像畸变,进一步提高地铁列检产品在车辆变速时的检测精度。在上海地铁17号线朱家角站的实际测试结果表明,由该技术获取的地铁车辆线扫图像不会因车速的变化而产生明显畸变,而且测速频率高,测试误差在1.2 km/h以内。

Aiming at the problem that some artificial intelligence-based subway vehicle train inspection products in the current rail transit market have low detection accuracy when the vehicle is shifting,a computer vision-based subway speed measurement method is proposed.First,the corrected subway image is obtained through image perspective transformation,and on the basis of the corrected image,the deep learning target detection method is used to locate the subway area.Second,feature point detection is performed on the subway area located in the adjacent two frames of images,and the matching point pair is obtained by using the strongest feature point matching method in the region.Then,the average pixel distance of the subway movement is calculated according to the matching point pair,and the actual moving distance is converted by combining the pixel size.Then,the current real-time speed of the subway can be obtained through the known time difference between two adjacent frames of images.Finally,according to the speed information detected in real time,the line frequency of the line scan camera is adjusted in real time,so as to reduce the image distortion caused by the speed change or parking of the subway vehicle as much as possible.Further improve the detection accuracy of subway train inspection products when the vehicle is shifting.The actual test results at Zhujiajiao Station of Shanghai Metro Line 17 show that the line scan images of subway vehicles obtained by this technology will not be significantly distorted due to changes in vehicle speed.Moreover,the speed measurement frequency is high,and the test error is within 1.2 km/h.