物探化探计算技术2026，Vol.48Issue(3)：395-403,9.DOI:10.12474/wthtjs.20250219-0001
基于凹凸特征的复杂岩石体点云配准算法研究与应用
Complex rock surface point cloud registration algorithm based on concave-convex feature encoding
摘要
Abstract
This paper introduces an advanced point cloud registration algorithm for rock masses,addressing challenges such as low overlap rates and complex feature distributions in complex geological environments.The method employs the Robust Neighbor Reweighted Local Centroid(RNRLC)technique,combined with a classification mechanism,to extract concave-convex feature points and construct descriptors based on spatial distance and concave-convex information.An optimized clustering mechanism enhances descriptor reliability while suppressing noise and local anomalies.Correspondences are identified via edit distance,and congruent triangles are constructed to compute the transformation matrix.A two-stage dynamic parameter adjustment ensures robust alignment,applying the transformation to the entire point cloud.Experiments show the proposed method outperforms traditional algorithms,such as ICP and CCEE,in scenarios with low overlap and large angular deviations,offering a reliable solution for point cloud registration in complex geological settings.关键词
岩石表层/点云配准/特征提取/特征描述符/DBSCAN聚类Key words
rock surface/point cloud registration/feature extraction/feature descriptor/DBSCAN clustering分类
信息技术与安全科学引用本文复制引用
孙红亮,陈亚军,陈思宇,张礼兵,高浩志..基于凹凸特征的复杂岩石体点云配准算法研究与应用[J].物探化探计算技术,2026,48(3):395-403,9.基金项目
中国电力建设集团科技项目(DJ-HXGG-2022-03) （DJ-HXGG-2022-03）
云南省数字水工程技术创新中心项目(202305AK340003) （202305AK340003）
