Research on Fast Pre-Processing Method of Tunnel Point Cloud Data in Complex Environment
Auteur(s): |
Ming Zhu
Biao Leng Chunhong Xiao Gaopeng Hou Xiangchen Yao Kai Li |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Journal of Physics: Conference Series, 1 janvier 2022, n. 1, v. 2185 |
Page(s): | 012038 |
DOI: | 10.1088/1742-6596/2185/1/012038 |
Abstrait: |
In recent years, the application and research of three-dimensional laser scanning technology in tunnel engineering has continuously emerged, while the shortcomings still exists. This paper conducts research on quick preprocessing method of tunnel point cloud data based on three-dimensional laser scanning. For streamlining the tunnel point cloud model data, comparison analysis discusses are applied to both the downsampling algorithm and the point cloud denoising method respectively. Simulation experiments are introduced to compare the effects of different downsampling algorithms applied to the tunnel point cloud model, analyze the sampling efficiency and performance of each algorithm. Combining with statistical denoising and radius denoising algorithms, a distance denoising based on an iterative filtering model method is proposed. The result shows that this method is suitable for the tunnel point cloud model during the construction period with complex environment, and can effectively eliminate most of the point cloud noise. |
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sur cette fiche - Reference-ID
10670919 - Publié(e) le:
12.06.2022 - Modifié(e) le:
12.06.2022