摘要
点云数据的分割是点云数据处理流程中的重要内容,同时也是点云数据三维重建的前提和基础。该研究在模糊C-均值聚类(FCM)算法的基础上,根据标靶点云和建筑物点云数据的不同特征进行实验,通过Matlab对地面雷达的标靶、建筑物点云数据进行分割,探讨模糊C-均值聚类算法对点云数据分割的可行性。实验结果显示,通过选择正确点云数据的特征属性,利用模糊C-均值算法对点云数据分割具有一定的可行性。
Point cloud data segmentation is an important part of the point cloud data processing flow, but also the premise and basis of three-di- mensional reconstruction of point cloud data. Based on the fuzzy C- means clustering （FCM） algorithm, according to different characteristics of the target point cloud and building point cloud data, the target of the ground radar and buildings point cloud data was segmented with Madab, the feasibility of fuzzy C- means clustering algorithm to segment the point cloud data was explored. The experimental results show that, by choosing the correct feature point cloud data, using the fuzzy C- mean algorithm has certain feasibility of point cloud data segmentation.
出处
《安徽农业科学》
CAS
2015年第17期353-356,共4页
Journal of Anhui Agricultural Sciences
关键词
点云数据分割
特征
模糊C-均值聚类
可行性
Point cloud data segmentation
Feature
Fuzzy C- means clustering
Feasibility
