基于PCA法向量估计与RANSAC算法的隧道中轴线提取Tunnel Axis Extraction Based on PCA Normal Vector Estimation with RANSAC Algorithm
陈昌文,潘国兵,张帅,敖其勇,袁小彬,熊延,龚洲
摘要(Abstract):
为了减少隧道点云噪声对隧道中轴线提取精度的影响,提出主成分分析(PCA,Principal Components Analysis)算法点云法向量估计与随机抽样一致性(RANSAC,Random Sample Consensus)算法相结合的隧道中轴线提取方法。首先对隧道点云数据进行ROI(Region of Interest)区域提取及统计滤波预处理,其次通过PCA算法估计隧道点云法向量并进行点云法向量方向一致化处理,通过设定阈值分别提取满足要求的隧道拱顶及拱腰处法向量,最后用RANSAC算法代替最小二乘算法对筛选出来的法向量提取出精度较高的隧道中轴线。实验结果表明,本文方法所提取出来的隧道中轴线受噪声影响较小,斜率最大偏差0.007 1,最小偏差0.000 3,算法稳定性好,结果精度较高。
关键词(KeyWords): 主要成分分析算法;点云法向量;随机抽样一致性算法;隧道中轴线提取
基金项目(Foundation): 广西空间信息与测绘重点实验室资助课题(19-050-11-04);; 城市空间信息工程北京市重点实验室经费资助项目(2020211)
作者(Author): 陈昌文,潘国兵,张帅,敖其勇,袁小彬,熊延,龚洲
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