高斯函数约束下的多判别参数散乱点云边缘检测

设计一种散乱点云数据边缘检测算法,从而快速、精确地提取边缘特征.该算法以点云的局部特征为基础,通过分析点云数据各点的法向特性,构建各点k近邻法向夹角特征、曲率特征、距离特征,并在高斯函数的约束下完成点云边缘特征的检测.利用公共数据进行多组实验,对比不同算法下的检测效果.结果表明:该算法提取点云边缘特征的速度更快、效果更好.

Multi-Discrimination Parameter Scattered Point Cloud Edge Detection Under Constraint of Gaussian Function

A scattered point cloud data edge detection algorithm is designed to extract edge features quickly and accurately. The algorithm is based on the local characteristics of the point cloud. By analyzing the characteristics of the normal vector of each point of the point cloud data, the k-nearest neighbor normal angle feature, the curvature feature, and the distance feature of each point are constructed to complete the point cloud edge feature detection under the constraint of the Gaussian function. Using public data to conduct multiple sets of experiments to compare the detection effects of different algorithms. The results show that the proposed algorithm is faster and better at extracting edge features of point clouds.