{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:00:54Z","timestamp":1760058054896,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T00:00:00Z","timestamp":1741564800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42171428","42271447","CKWV20231177\/KY"],"award-info":[{"award-number":["42171428","42271447","CKWV20231177\/KY"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"CRSRI Open Research Program","award":["42171428","42271447","CKWV20231177\/KY"],"award-info":[{"award-number":["42171428","42271447","CKWV20231177\/KY"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Point cloud data are often accompanied by noise and irregularities, which bring great challenges to the extraction of point cloud surface traces of discontinuous rock masses. Most of the existing feature line extraction methods rely on traditional geometric or statistical techniques, which are less resistant to noise. To address this issue, this paper proposes a novel method for trajectory recognition on discontinuous surfaces of rock mass point clouds. The method first detects and extracts the trajectory feature points using normal tensor voting theory based on the symmetry of the point cloud at different periods. Then, three steps of grouping, trace segment growth, and inter-group connection are used to extract discontinuous traces from the feature points. The experimental results show that the optimal triangular grid cell size in this paper is between 5 cm and 7 cm; the optimal range of the angle threshold is between 70\u00b0 and 90\u00b0; the optimal range of the angle threshold is between 50\u00b0 and 60\u00b0; and the value of the distance threshold should be at least 15 times the size of the triangular grid cell. The method in this paper can still maintain a high accuracy and stability in noisy rock mass point cloud data, and has a strong potential for practical application.<\/jats:p>","DOI":"10.3390\/sym17030415","type":"journal-article","created":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T08:46:41Z","timestamp":1741596401000},"page":"415","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Trace Recognition of Rock Mass Point Clouds by the Fusion of Normal Tensor Voting and a Minimum Spanning Tree"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2753-2854","authenticated-orcid":false,"given":"Xijiang","family":"Chen","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Wuchang University of Technology, Wuhan 430223, China"},{"name":"School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3219-2591","authenticated-orcid":false,"given":"Qing","family":"An","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Wuchang University of Technology, Wuhan 430223, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianquan","family":"Han","sequence":"additional","affiliation":[{"name":"Changjiang River Scientific Research Institute, Wuhan 430010, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hu, Q., Ma, C., Bai, Y., He, L., Tan, J., Cai, Q., and Zeng, J. 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