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Proceedings Paper

An unorganized point cloud simplification based on boundary point extraction
Author(s): Xiao-qi Lan; Hong Zhang; Bing-bing Duan
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Paper Abstract

In the reverse engineering, the dense and disordered point cloud data contain a huge number of redundancy, which inevitably leads to the significant challenges for the tasks of the subsequent data processing. This paper presents a single axis searching arithmetic to obtain the neighborhood information of a point cloud, and then based on all boundary points extracted and reserved, a non-uniform data reduction scheme, according to a specified curvature threshold and the proportion of reserved points in the k-nearest neighbors, is proposed. The experimental result shows that this approach has a strong ability for identifying boundary points, and can directly and effectively reduce the point cloud data, meanwhile keep the original geometric feature.

Paper Details

Date Published: 24 October 2011
PDF: 9 pages
Proc. SPIE 8286, International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications, 828618 (24 October 2011); doi: 10.1117/12.912977
Show Author Affiliations
Xiao-qi Lan, Hohai Univ. (China)
Hong Zhang, Hohai Univ. (China)
Bing-bing Duan, Hohai Univ. (China)


Published in SPIE Proceedings Vol. 8286:
International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications
Jonathan Li, Editor(s)

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