Extraction of cavern surface deformation regions based on Alpha Shapes contour point cloud recognition algorithm
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TP391.41

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    Abstract:

    Aiming at the extraction of cavern surface deformation from three-dimensional laser scanning dense point clouds,we propose a method integrating the Multiscale Model-to-Model Cloud Comparison (M3C2) with an improved Alpha Shapes algorithm.First,the two-phase surface point cloud data are registered,and the improved Alpha Shapes algorithm is used to identify the outer contour point clouds.After the fine registration of these two-phase outer contour point clouds,the M3C2 algorithm calculates the deformation value of each point,and finally the continuous deformation regions are extracted through distance clustering.Experimental results show that the proposed method effectively eliminates the points at small furrows as well as those affected by mixed pixels.Specifically,the removal rates of point clouds in the two phases within 10 m from the scanner to the cavern section are 14.17% and 13.52%,respectively,which are 6.25% and 6.42% within 70 m.This method accurately and efficiently extracts the cavern surface deformation regions with more than twice the registration error.

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ZHANG Yuting, ZHENG Dehua, LI Siyuan. Extraction of cavern surface deformation regions based on Alpha Shapes contour point cloud recognition algorithm[J]. Journal of Nanjing University of Information Science & Technology,2025,17(2):181-190

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History
  • Received:May 13,2024
  • Online: April 16,2025
  • Published: March 28,2025
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