基于型面特征的三维散乱点云精简算法

Reduction Algorithm for Scattered Points Based on Model Surface Analysis

提出一种基于局部型面特征的散乱点云精简算法,该算法采用R*-tree建立点云动态空间索引结构,基于该结构快速准确获取点云局部型面参考数据;采用自由曲面逼近该数据并估算该数据的曲率,依据曲率分布状况精简点云数据。实例证明,该算法可在保留点云型面特征的基础上,快速有效地对点云进行精简。

A new reduction algorithm for scattered points based on local surface feature was proposed.First,a dynamic spatial index structure of scattered points was established with R＊-tree.Second,the local surface reference data was obtained based on the spatial index structure.Third,the local surface reference data was approached with free-form surface,and its curvature was computed.Fourth,the reduction of scattered points was realized based on its model curvature.It is proved that this algorithm can reduce point-data effectively under the conditions that preserve the surface characteristics of scattered points.