计算机工程与应用2024，Vol.60Issue(11)：233-241,9.DOI:10.3778/j.issn.1002-8331.2302-0054
机载LiDAR点云数据的建筑屋顶面提取算法
Algorithm for Extracting Building Roof Surfaces from Airborne LiDAR Point Cloud Data
摘要
Abstract
A region-growing-based point cloud extraction algorithm for roof surfaces is proposed to address the issue of low extraction accuracy caused by vegetation interference in airborne LiDAR point cloud data.Firstly,the filtering treat-ment is conducted to obtain the non-ground point cloud.Then,the neighborhood feature information of the roof point is used to extract roof surface seed points,in which the vegetation index and RGB difference information are introduced as growth constraints to segment the roof surface point cloud.Finally,the extracted results are filtered and optimized by using the elevation and area values of the roof surface to get the point cloud of the roof surface.The experiment is carried out by selecting three groups of test data from different scenarios,such as rural areas,urban and factory.In accordance with the results,it indicates that the Kappa coefficients reach 97.29%,97.82%and 97.13%respectively,a relatively better building roof surface extraction effect can be realized,and a good adaptability for different building scenes is embodied.关键词
机载LiDAR/屋顶面提取/邻域信息/区域生长/植被指数Key words
aerial LiDAR/roof surface extraction/neighborhood information/region growing/vegetation index分类
天文与地球科学引用本文复制引用
李海旺,周恒可,赵兴,郭彩玲,李柏林..机载LiDAR点云数据的建筑屋顶面提取算法[J].计算机工程与应用,2024,60(11):233-241,9.基金项目
河北省高层次人才项目(A202001095) （A202001095）
河北省科技厅重点研发计划(20327407D). （20327407D）
