A Novel Type of Boundary Extraction Method and Its Statistical Improvement for Unorganized Point Clouds Based on Concurrent Delaunay Triangular Meshes
Currently, three-dimensional (3D) laser-scanned point clouds have been broadly applied in many important fields, such as non-contact measurements and reverse engineering. However, it is a huge challenge to efficiently and precisely extract the boundary features of unorganized point cloud data with s...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/4/1915 |
| _version_ | 1827755616317210624 |
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| author | Xiuzhi He Rongqi Wang Chao Feng Xiaoqin Zhou |
| author_facet | Xiuzhi He Rongqi Wang Chao Feng Xiaoqin Zhou |
| author_sort | Xiuzhi He |
| collection | DOAJ |
| description | Currently, three-dimensional (3D) laser-scanned point clouds have been broadly applied in many important fields, such as non-contact measurements and reverse engineering. However, it is a huge challenge to efficiently and precisely extract the boundary features of unorganized point cloud data with strong randomness and distinct uncertainty. Therefore, a novel type of boundary extraction method will be developed based on concurrent Delaunay triangular meshes (CDTMs), which adds the vertex-angles of all CDTMs around a common data point together as an evaluation index to judge whether this targeted point will appear at boundary regions. Based on the statistical analyses on the CDTM numbers of every data point, another new type of CDTM-based boundary extraction method will be further improved by filtering out most of potential non-edge points in advance. Then these two CDTM-based methods and popular <i>α</i>-shape method will be employed in conducting boundary extractions on several point cloud datasets for comparatively analyzing and discussing their extraction accuracies and time consumptions in detail. Finally, all obtained results can strongly demonstrate that both these two CDTM-based methods present superior accuracies and strong robustness in extracting the boundary features of various unorganized point clouds, but the statistically improved version can greatly reduce time consumption. |
| first_indexed | 2024-03-11T08:10:29Z |
| format | Article |
| id | doaj.art-0e895df0a592459889ec5c1c3a23c95a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T08:10:29Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0e895df0a592459889ec5c1c3a23c95a2023-11-16T23:07:50ZengMDPI AGSensors1424-82202023-02-01234191510.3390/s23041915A Novel Type of Boundary Extraction Method and Its Statistical Improvement for Unorganized Point Clouds Based on Concurrent Delaunay Triangular MeshesXiuzhi He0Rongqi Wang1Chao Feng2Xiaoqin Zhou3Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun 130025, ChinaKey Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun 130025, ChinaKey Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun 130025, ChinaKey Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun 130025, ChinaCurrently, three-dimensional (3D) laser-scanned point clouds have been broadly applied in many important fields, such as non-contact measurements and reverse engineering. However, it is a huge challenge to efficiently and precisely extract the boundary features of unorganized point cloud data with strong randomness and distinct uncertainty. Therefore, a novel type of boundary extraction method will be developed based on concurrent Delaunay triangular meshes (CDTMs), which adds the vertex-angles of all CDTMs around a common data point together as an evaluation index to judge whether this targeted point will appear at boundary regions. Based on the statistical analyses on the CDTM numbers of every data point, another new type of CDTM-based boundary extraction method will be further improved by filtering out most of potential non-edge points in advance. Then these two CDTM-based methods and popular <i>α</i>-shape method will be employed in conducting boundary extractions on several point cloud datasets for comparatively analyzing and discussing their extraction accuracies and time consumptions in detail. Finally, all obtained results can strongly demonstrate that both these two CDTM-based methods present superior accuracies and strong robustness in extracting the boundary features of various unorganized point clouds, but the statistically improved version can greatly reduce time consumption.https://www.mdpi.com/1424-8220/23/4/1915point cloud data3D laser scanningboundary extractionDelaunay triangular meshesstatistical characteristics |
| spellingShingle | Xiuzhi He Rongqi Wang Chao Feng Xiaoqin Zhou A Novel Type of Boundary Extraction Method and Its Statistical Improvement for Unorganized Point Clouds Based on Concurrent Delaunay Triangular Meshes Sensors point cloud data 3D laser scanning boundary extraction Delaunay triangular meshes statistical characteristics |
| title | A Novel Type of Boundary Extraction Method and Its Statistical Improvement for Unorganized Point Clouds Based on Concurrent Delaunay Triangular Meshes |
| title_full | A Novel Type of Boundary Extraction Method and Its Statistical Improvement for Unorganized Point Clouds Based on Concurrent Delaunay Triangular Meshes |
| title_fullStr | A Novel Type of Boundary Extraction Method and Its Statistical Improvement for Unorganized Point Clouds Based on Concurrent Delaunay Triangular Meshes |
| title_full_unstemmed | A Novel Type of Boundary Extraction Method and Its Statistical Improvement for Unorganized Point Clouds Based on Concurrent Delaunay Triangular Meshes |
| title_short | A Novel Type of Boundary Extraction Method and Its Statistical Improvement for Unorganized Point Clouds Based on Concurrent Delaunay Triangular Meshes |
| title_sort | novel type of boundary extraction method and its statistical improvement for unorganized point clouds based on concurrent delaunay triangular meshes |
| topic | point cloud data 3D laser scanning boundary extraction Delaunay triangular meshes statistical characteristics |
| url | https://www.mdpi.com/1424-8220/23/4/1915 |
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