A pothole detection method based on 3D point cloud segmentation

Ying Du; Zuofeng Zhou; Qingquan Wu; Huimin Huang; Mingming Xu; Jianzhong Cao; Guoliang Hu

doi:10.1117/12.2573124

12 June 2020 A pothole detection method based on 3D point cloud segmentation

Ying Du, Zuofeng Zhou, Qingquan Wu, Huimin Huang, Mingming Xu, Jianzhong Cao, Guoliang Hu

Proceedings Volume 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020); 1151909 (2020) https://doi.org/10.1117/12.2573124
Event: Twelfth International Conference on Digital Image Processing, 2020, Osaka, Japan

Abstract

Road potholes affect comfort, safety, traffic condition and vehicle stability. Accurately detecting these potholes is vital for assessing the degree of pavement distress and developing road maintenance plan accordingly. This paper proposes a simple and effective pothole detection method based on 3D point cloud segmentation. Using binocular stereo vision to acquire 3D point clouds, fitting the pavement plane and then eliminating it from the 3D point clouds of road scene, we could roughly extract the pothole. K-means clustering and region growing algorithms were adopted to extract the potholes precisely. The experimental results demonstrate that our proposed method has a very good segmentation effect on scenes involving plane and target object.

Citation Download Citation

Ying Du, Zuofeng Zhou, Qingquan Wu, Huimin Huang, Mingming Xu, Jianzhong Cao, and Guoliang Hu "A pothole detection method based on 3D point cloud segmentation", Proc. SPIE 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020), 1151909 (12 June 2020); https://doi.org/10.1117/12.2573124

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