植物三维点云分割  

Three-Dimensional Point Cloud Segmentation for Plants

作　　者：赖亦斌 陆声链[1,2] 钱婷婷[3] 宋真[1] 陈明 LAI Yibin;LU Shenglian;QIAN Tingting;SONG Zhen;CHEN Ming(College of Computer Science and Technology,Guangxi Normal University,Guilin 541004,Guangxi,China;Guangxi Key Lab of Multi-source Information Mining&Security,Guilin 541004,Guangxi,China;Institute of Agricultural Science and Technology Information,Shanghai Academy of Agriculture Sciences,Shanghai 201403,China)

机构地区：[1]广西师范大学计算机科学与工程学院,广西桂林541004 [2]广西师范大学广西多源信息挖掘与安全重点实验室,广西桂林541004 [3]上海市农业科学院农业科技信息研究所,上海201403

出　　处：《应用科学学报》2021年第4期660-671,共12页Journal of Applied Sciences

基　　金：国家自然科学基金(No.61762013);上海市科技兴农重点攻关项目基金(No.G2015060402);广西教育厅项目基金(No.2018KY0078)资助。

摘　　要：针对植物点云具有形状不规则、密度不均匀的特点,提出一种适用于植物的三维点云分割方法。将烟草、玉米、黄瓜这3种植物作为样本数据,以滤波等预处理方法去除离群点与背景点,以欧氏聚类算法分割植物群体,并用区域增长算法、边缘提取算法、超体素聚类算法以及基于凹凸性的方法来分割叶片器官。将所提出的方法用于分割烟草、玉米的三维点云,其覆盖率分别为87.5%、96.9%,从而验证了该方法的可行性与有效性,为自动提取作物叶器官表型研究提供了线索。Aiming at the irregular shape and uneven density of plant point clouds,a three-dimensional point cloud segmentation method applied to plants is proposed.Three plants of tobacco,corn,and cucumber are used as sample data,in which outliers and background points are removed by filtering and other preprocessing methods.Plant population is segmented by the Euclidean clustering algorithm,and leaf organs are segmented by region growing algorithm,edge extraction algorithm,super voxel clustering algorithm,and segmentation algorithm based on unevenness.The proposed method is used to segment three-dimensional point clouds of tobacco and corn,and the coverage rates are 87.5%and 96.9%,respectively.This verifies the feasibility and effectiveness of the method and provides clues for the automatic extraction of plant leaf organ phenotypes.

关 键 词：三维点云 植物表型 点云分割 叶片分割 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]