面向智慧交通的移动激光点云树木分割

Abstract

单树分割有利于提取交通标志牌,减少对交通标志的遮挡影响.针对有效采集到的道路两旁树木的点云数据,提出了一种改进的分水岭车载激光扫描的树木分割方法; .该方法包含5个步骤:1)利用RANSAC(random sample; consensus)自动检测和剔除地面点;2)压缩所有地面点到图像网格并保留三维信息;3)简化和去除不合格网格;4)利用启发式搜索方法查找树峰;; 5)应用改进分水岭方法划分单树树冠.通过对福建省厦门市环岛路进行实地采集的点云数据进行实验,验证了所提出的分割模型对于车载林木点云数据具有较好的; 分割结果.

With the development of light detection and ranging (LiDAR); technology,3-dimenisonal (3D) structure of trees can be generated in; point clouds with high spatial resolution and accuracy.Individual tree; segmentations are used to derive tree structural attributes such as tree; height,crown diameter,and stem position among others.In this study,a; framework is proposed to take advantage of the detailed structures of; tree crowns which are represented in the mobile laser scanning (MLS); data.This framework consists of five steps:1) Automatically detect and; remove ground points using RANSAC;2) Compress all the above-ground; points to image grid with 3D knowledge reserved;3) Simplify and remove; unqualified grids;4) Find tree peaks by using a heuristic searching; method;5) Delineate individual tree crowns by applying a modified; watershed method.In an experiment on the point clouds on Xiamen; Island,China,individual tree crowns from MLS point cloud data are; successfully extracted.