密度聚类方法在点云数据分割中的应用研究

The Application of Density Clustering Method in the Point Cloud Data Segmentation

点云数据分割是点云数据处理的主要工作,也是实现地物自动识别的前提和关键环节,由于各种原因,目前点云数据分割自动化程度不高,尚需进一步的深入研究。本文以机载云数据为研究对象,提出了基于密度聚类方法的激光点云数据分割方法,该方法具有速度快、分割效果好、适应性强等优势,为后续的地物自动识别奠定了基础。

Point cloud data segmentation is a major work of point cloud data processing and it is also the premise and key step to a -chieve automatic object recognition .However, due to various reasons the degree of automatic point cloud segmentation is not very high, further study is still needed .In this paper, the density clustering methods in laser point cloud data segmentation is presented and experiments have been done on airborne cloud data .The result shows that this method has higher speed , better segmentation re-sults, more applicable and other advantages .The method laid the foundation for subsequent automatic object recognition in the fea -ture.