中图分类号：TP391
文献标识码：A
DOI： 10.19358/j.issn.2096-5133.2020.02.006
引用格式：周建钊，颜雨吉,陈晨，等.一种邻域自适应的双阈值点云特征提取方法［J］.信息技术与网络安全，2020,39（2）：27-33.

A twothreshold point cloud feature extraction method with neighborhood adaptive

Abstract： The feature extraction of point cloud data is an important part of point cloud data processing,which plays a key role in geometric analysis,data segmentation,point cloud registration,and model reconstruction.The point cloud feature extraction technology based on normal vector and curvature has been studied.The problems of neighborhood selection and single parameter calculation in the feature extraction process are clarified.A twothreshold point cloud feature extraction method with adaptive neighborhood is proposed.The experiment compares the extraction effect of the algorithm with the curvaturebased feature extraction algorithm,and verifies the stability and accuracy of the algorithm.This algorithm has a good extraction effect for point clouds with complex geometric features,and has important significance for improving the accuracy and efficiency of point cloud feature point extraction.

Key words : point cloud feature extraction;normal vector;curvature;double threshold;neighborhood adaptive