测绘与空间地理信息
測繪與空間地理信息
측회여공간지리신식
GEOMATICS & SPATIAL INFORMATION TECHNOLOGY
2015年
1期
44-47
,共4页
LiDAR%点云%密度聚类%自动分割
LiDAR%點雲%密度聚類%自動分割
LiDAR%점운%밀도취류%자동분할
LiDAR%point cloud%density clustering%automatic 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。
點雲數據分割是點雲數據處理的主要工作,也是實現地物自動識彆的前提和關鍵環節,由于各種原因,目前點雲數據分割自動化程度不高,尚需進一步的深入研究。本文以機載雲數據為研究對象,提齣瞭基于密度聚類方法的激光點雲數據分割方法,該方法具有速度快、分割效果好、適應性彊等優勢,為後續的地物自動識彆奠定瞭基礎。
점운수거분할시점운수거처리적주요공작,야시실현지물자동식별적전제화관건배절,유우각충원인,목전점운수거분할자동화정도불고,상수진일보적심입연구。본문이궤재운수거위연구대상,제출료기우밀도취류방법적격광점운수거분할방법,해방법구유속도쾌、분할효과호、괄응성강등우세,위후속적지물자동식별전정료기출。
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.