北京林业大学学报2016，Vol.38Issue(5)：133-138,6.DOI:10.13332/j.1000--1522.20150332
基于特征融合的林下环境点云分割
Point cloud segmentation algorithm based on feature fusion used for understory environments. Jo
摘要
Abstract
Aimed at the complexity of geometric features of understory environments and the deficiency of edge detection based method, region growing based method and clustering feature based method, we propose a new point cloud segmentation algorithm based on feature fusion. The 3D data set acquired from Beijing Forestry University using a FARO laser scanner consists of 1 166 302 points after removing outliers and filtering. The data set has four targets, i. e. , tree, ground, stone and person. Point cloud segmentation can be achieved via fusing normal vector and laser reflection intensity of each point. The laser reflection intensity values can be obtained from point cloud data set directly, and normal vector should be calculated based on the Plane PCA algorithm. Also, it is necessary to create kd-tree data structure and perform k-NN search during the calculation of normal vector. Segmentation is realized after fusing the advantages of normal vector and laser reflection intensity and calculating synthetical difference degree between query points and neighborhood points. Comparing the segmentation results from point cloud segmentation algorithms based on feature fusion, normal vector and laser reflection intensity, the method based on feature fusion overcomes the problem of data deficiency that the other two methods suffer.关键词
林下环境/点云分割/法向量/激光强度Key words
understory environment/point cloud segmentation/normal vector/laser reflection intensity分类
农业科技引用本文复制引用
樊丽,刘晋浩,黄青青..基于特征融合的林下环境点云分割[J].北京林业大学学报,2016,38(5):133-138,6.基金项目
“948”国家林业局引进项目(2011-4-02)。 （2011-4-02）
