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基于法向量夹角的果树点云配准与枝叶分割方法研究

韩宏琪 江自真 周俊 顾宝兴

农业机械学报2024,Vol.55Issue(9):327-336,10.
农业机械学报2024,Vol.55Issue(9):327-336,10.DOI:10.6041/j.issn.1000-1298.2024.09.028

基于法向量夹角的果树点云配准与枝叶分割方法研究

Fruit Tree Point Cloud Registration Based on Normal Vector Angles and Branch-Leaf Segmentation Method

韩宏琪 1江自真 1周俊 1顾宝兴1

作者信息

  • 1. 南京农业大学工学院,南京 210031
  • 折叠

摘要

Abstract

In realizing full automation of orchard operations,it is urgent to construct a 3D model of fruit tree branches and trunks in the natural environment directly.Point clouds of fruit trees collected from different views in the natural environment were registered.Considering that sampling consistency(SAC-IA)+iterative nearest point(ICP)registration algorithm took a long time and had low accuracy in point cloud registration.Thus,the feature points of the source point cloud and target point cloud were extracted by combining the angle of the normal vector of the point cloud,and then matching point pairs were found in the feature points of the source and target point clouds based on the cosine value of the angle of the normal vector of the point cloud.Using the matching point pairs of fruit tree point clouds,an improved SAC-IA+ICP point cloud registration algorithm was proposed.Further,the registered fruit tree point cloud was partitioned by using the partitioning technology of minimum box partition,and then the branches and leaves of the partitioned sub-blocks were roughed by using the geometric features of the point cloud;finally,the branches and leaves were partitioned by using Euclidean clustering.Compared with the original SAC-IA+ICP algorithm,the average rotation error was reduced by 85.44%,and the registration root mean square error can be reduced by 71.74%,the registration time was reduced by 97.99%.Meantime,compared with the SAC-IA+NDT algorithm,the average rotation error was reduced by 90.38%,and the registration root mean square error can be reduced by 85.39%,the registration time was reduced by 98.04%.The segmentation algorithm can complete the segmentation of branches and leaves,and the accuracy can reach 94.77%compared with manual segmentation.

关键词

果树/点云/法向量夹角/点云配准/枝叶分割

Key words

fruit trees/point cloud/normal vector angle/point cloud registration/branch-leaf segmentation

分类

信息技术与安全科学

引用本文复制引用

韩宏琪,江自真,周俊,顾宝兴..基于法向量夹角的果树点云配准与枝叶分割方法研究[J].农业机械学报,2024,55(9):327-336,10.

基金项目

江苏省现代农机装备与技术示范推广项目(NJ2022-14)和江苏省重点研发计划项目(BE2017370) (NJ2022-14)

农业机械学报

OA北大核心CSTPCD

1000-1298

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