点云模型特征面分割与识别方法  

Feature Surface Segmentation and Recognition Method for Point Cloud Model

作　　者：袁小翠[1] 陈华伟 YUAN Xiaocui;CHEN Huawei(Jiangxi Province Key Laboratory of Precision Drive and Control,Nanchang Institute of Technology,Nanchang 330099,China;School of Mechanical and Electrical Engineering,Guizhou Normal University,Guiyang 550025,China)

机构地区：[1]南昌工程学院江西省精密驱动与控制重点实验室,南昌330099 [2]贵州师范大学机电工程学院,贵阳550025

出　　处：《计算机工程》2018年第11期245-250,共6页Computer Engineering

基　　金：国家自然科学基金(51365037);江西省教育厅科学技术研究项目(GJJ61122)

摘　　要：针对点云模型分割和特征面识别速度慢、准确性差的问题,提出基于连通区域标记和统计法的散乱点云特征面分割与识别方法。通过估算点云法矢与点云曲率,给出零值固定曲率归一化方法。基于曲率对点云初始聚类,采用连通区域标记法分割点云,进而利用统计法判断点云所属特征类型曲面。实验结果表明,在以规则曲面为主的机械零件特征曲面分割和识别应用中,该方法能够满足中小型规模的点云处理需求。Aiming at the problem of slow speed and poor accuracy of model segmentation and feature surface recognition,a point cloud segmentation and surface recognition method based on connected component labeling and probabilistic method is proposed.A zero-value fixed curvature normalization method is proposed by estimating the curvature of the point cloud and the curvature of the point cloud.Based on the initial clustering of curvature on the point cloud,the connected region marker method is used to segment the point cloud,and then the statistical method is used to judge the feature type surface of the point cloud.Experimental results show that the proposed method can meet the demand for processing small and medium size point clouds in the segmentation and application of feature surface of mechanical parts based on regular surfaces.

关 键 词：点云分割 法矢估计 曲率估算 曲面识别 特征曲面 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]