Journal of Northeastern University(Natural Science) ›› 2021, Vol. 42 ›› Issue (9): 1323-1328.DOI: 10.12068/j.issn.1005-3026.2021.09.015

• Resources & Civil Engineering • Previous Articles     Next Articles

Step Line Extraction from Point Cloud Data of Open-Pit Mine

WANG Zhi, AN Shi-yuan, ZOU Jun, ZHANG Zi-rui   

  1. School of Resources & Civil Engineering,Northeastern University,Shenyang 110819,China.
  • Revised:2020-10-12 Accepted:2020-10-12 Published:2021-09-16
  • Contact: WANG Zhi
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Abstract: The information of step line is of great importance to open-pit mining. The existing method of obtaining step line has large workload, low efficiency and poor accuracy, which reduces the production efficiency and acceptance accuracy of the mine.Thus, a method of automatically extracting open-pit mine step lines from the dense point cloud data of open-pit mines generated by sequence UAV images is proposed in this paper. This method uses progressive morphological filtering algorithm to preprocess the point cloud, and a three-dimensional edge detection and curvature index weighting method that takes into account the geometric properties of the neighborhood is proposed to extract the feature points of the step line, then, it uses the moving least squares method to accurately fit the step line. The experimental results show that the algorithm can automatically, efficiently and accurately extract the step line of the open-pit mine, and generate open-pit mining status map. It has important application value for open-pit mine production and safety.

Key words: open-pit mines; step line; 3D point cloud; curvature; automatic extraction

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