Xu Yi, Sun Teng, Ding Shaohong, Yu Jinxin, Kong Xiangcun, Ni Juan, Shi Shuyue
School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China.
Collaborative Innovation Center of New Energy Automotive, Shandong University of Technology, Zibo 255000, China.
Sensors (Basel). 2023 Aug 28;23(17):7468. doi: 10.3390/s23177468.
This paper presents a VIDAR (a Vision-IMU based detection and ranging method)-based approach to road-surface pothole detection. Most potholes on the road surface are caused by the further erosion of cracks in the road surface, and tires, wheels and bearings of vehicles are damaged to some extent as they pass through the potholes. To ensure the safety and stability of vehicle driving, we propose a VIDAR-based pothole-detection method. The method combines vision with IMU to filter, mark and frame potholes on flat pavements using MSER to calculate the width, length and depth of potholes. By comparing it with the classical method and using the confusion matrix to judge the correctness, recall and accuracy of the method proposed in this paper, it is verified that the method proposed in this paper can improve the accuracy of monocular vision in detecting potholes in road surfaces.
本文提出了一种基于VIDAR(一种基于视觉-惯性测量单元的检测和测距方法)的路面坑洼检测方法。路面上的大多数坑洼是由路面裂缝的进一步侵蚀造成的,车辆的轮胎、车轮和轴承在通过坑洼时会受到一定程度的损坏。为确保车辆行驶的安全性和稳定性,我们提出了一种基于VIDAR的坑洼检测方法。该方法将视觉与惯性测量单元相结合,利用最大稳定极值区域(MSER)在平坦路面上对坑洼进行滤波、标记和框选,以计算坑洼的宽度、长度和深度。通过与经典方法进行比较,并使用混淆矩阵来判断本文所提方法的正确性、召回率和准确率,验证了本文所提方法能够提高单目视觉检测路面坑洼的准确性。