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基于点云强度的公园乔木检测方法
引用本文:赵小祥,黄亮.基于点云强度的公园乔木检测方法[J].北京测绘,2020(3):292-295.
作者姓名:赵小祥  黄亮
作者单位:江苏省测绘工程院
摘    要:利用树干石灰涂层在激光点云中的高反射特性,本文提出一种基于点云强度的公园乔木检测方法。首先,使用三维激光扫描仪采集点云,并对点云进行去噪以及地面滤波。接着,对非地面点进行阈值分割,高强度部分包含了涂有石灰的树干。最后,对高强度点实施欧式聚类算法,通过尺寸与点数的约束,得到树干的聚类单元。通过实验证明,该方法具有自动化程度高、检测率高、误检率低等优势,满足公园调查的技术要求。

关 键 词:点云  乔木  强度  欧式聚类

Park Tree Survey Method Based on Laser Point Cloud
ZHAO Xiaoxiang,HUANG Liang.Park Tree Survey Method Based on Laser Point Cloud[J].Beijing Surveying and Mapping,2020(3):292-295.
Authors:ZHAO Xiaoxiang  HUANG Liang
Affiliation:(Jiangsu Institute of Surveying and Mapping Engineering, Nanjing Jiangsu 210013, China)
Abstract:Considering the high reflection characteristics of the lime coating of tree trunk in the laser point cloud,this paper proposes a method of park tree detection based on the point cloud intensity.Firstly,3d laser scanner is used to collect point cloud,and the point cloud is denoised and ground filtered.Then,intensity threshold segmentation was performed at non-ground points,with the high-intensity portion consisting of limed tree trunks.Finally,the euclidean clustering algorithm is implemented for the high-intensity point cloud,and the clustering unit of tree trunk is obtained through the constraint of size and number.The experimental results show that this method has the advantages of high automation,high detection rate and low false detection rate,and can meet the technical requirements of park investigation.
Keywords:point cloud  tree  intensity  euclidean clustering
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