Rock discontinuity extraction from 3D point clouds using pointwise clustering algorithm
Recognizing discontinuities within rock masses is a critical aspect of rock engineering. The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected from rock outcrops. In response, we propose a workflow that balances accuracy and...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-07-01
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| Series: | Journal of Rock Mechanics and Geotechnical Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1674775524004712 |
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| _version_ | 1839631290680213504 |
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| author | Xiaoyu Yi Wenxuan Wu Wenkai Feng Yongjian Zhou Jiachen Zhao |
| author_facet | Xiaoyu Yi Wenxuan Wu Wenkai Feng Yongjian Zhou Jiachen Zhao |
| author_sort | Xiaoyu Yi |
| collection | DOAJ |
| description | Recognizing discontinuities within rock masses is a critical aspect of rock engineering. The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected from rock outcrops. In response, we propose a workflow that balances accuracy and efficiency to extract discontinuities from massive point clouds. The proposed method employs voxel filtering to downsample point clouds, constructs a point cloud topology using K-d trees, utilizes principal component analysis to calculate the point cloud normals, and employs the pointwise clustering (PWC) algorithm to extract discontinuities from rock outcrop point clouds. This method provides information on the location and orientation (dip direction and dip angle) of the discontinuities, and the modified whale optimization algorithm (MWOA) is utilized to identify major discontinuity sets and their average orientations. Performance evaluations based on three real cases demonstrate that the proposed method significantly reduces computational time costs without sacrificing accuracy. In particular, the method yields more reasonable extraction results for discontinuities with certain undulations. The presented approach offers a novel tool for efficiently extracting discontinuities from large-scale point clouds. |
| format | Article |
| id | doaj-art-e8b30d8a8c9e4965aa49cc0d1a34d0e8 |
| institution | Matheson Library |
| issn | 1674-7755 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Rock Mechanics and Geotechnical Engineering |
| spelling | doaj-art-e8b30d8a8c9e4965aa49cc0d1a34d0e82025-07-12T04:46:04ZengElsevierJournal of Rock Mechanics and Geotechnical Engineering1674-77552025-07-0117744294444Rock discontinuity extraction from 3D point clouds using pointwise clustering algorithmXiaoyu Yi0Wenxuan Wu1Wenkai Feng2Yongjian Zhou3Jiachen Zhao4State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China; College of Environment and Civil Engineering, Chengdu University of Technology, Chengdu, 610059, ChinaCollege of Environment and Civil Engineering, Chengdu University of Technology, Chengdu, 610059, ChinaState Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China; College of Environment and Civil Engineering, Chengdu University of Technology, Chengdu, 610059, China; Corresponding author. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China.College of Environment and Civil Engineering, Chengdu University of Technology, Chengdu, 610059, ChinaCollege of Environment and Civil Engineering, Chengdu University of Technology, Chengdu, 610059, ChinaRecognizing discontinuities within rock masses is a critical aspect of rock engineering. The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected from rock outcrops. In response, we propose a workflow that balances accuracy and efficiency to extract discontinuities from massive point clouds. The proposed method employs voxel filtering to downsample point clouds, constructs a point cloud topology using K-d trees, utilizes principal component analysis to calculate the point cloud normals, and employs the pointwise clustering (PWC) algorithm to extract discontinuities from rock outcrop point clouds. This method provides information on the location and orientation (dip direction and dip angle) of the discontinuities, and the modified whale optimization algorithm (MWOA) is utilized to identify major discontinuity sets and their average orientations. Performance evaluations based on three real cases demonstrate that the proposed method significantly reduces computational time costs without sacrificing accuracy. In particular, the method yields more reasonable extraction results for discontinuities with certain undulations. The presented approach offers a novel tool for efficiently extracting discontinuities from large-scale point clouds.http://www.sciencedirect.com/science/article/pii/S1674775524004712Rock mass discontinuity3D point cloudsPointwise clustering (PWC) algorithmModified whale optimization algorithm (MWOA) |
| spellingShingle | Xiaoyu Yi Wenxuan Wu Wenkai Feng Yongjian Zhou Jiachen Zhao Rock discontinuity extraction from 3D point clouds using pointwise clustering algorithm Journal of Rock Mechanics and Geotechnical Engineering Rock mass discontinuity 3D point clouds Pointwise clustering (PWC) algorithm Modified whale optimization algorithm (MWOA) |
| title | Rock discontinuity extraction from 3D point clouds using pointwise clustering algorithm |
| title_full | Rock discontinuity extraction from 3D point clouds using pointwise clustering algorithm |
| title_fullStr | Rock discontinuity extraction from 3D point clouds using pointwise clustering algorithm |
| title_full_unstemmed | Rock discontinuity extraction from 3D point clouds using pointwise clustering algorithm |
| title_short | Rock discontinuity extraction from 3D point clouds using pointwise clustering algorithm |
| title_sort | rock discontinuity extraction from 3d point clouds using pointwise clustering algorithm |
| topic | Rock mass discontinuity 3D point clouds Pointwise clustering (PWC) algorithm Modified whale optimization algorithm (MWOA) |
| url | http://www.sciencedirect.com/science/article/pii/S1674775524004712 |
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