Segmentation wooden member from range images is the basis of 3d reconstruction of wooden member and whole architecture because it provides reliable point clouds for modeling. This paper presents a segmentation strategy to extract point clouds of wooden member of ancient architecture from range image. Hybrid approach combining edge and region-based techniques is adopted in the paper to ensure a reliable and robust segmentation. First, range image is triangulated according to the implied topological relationships between point clouds. Second, filtering is processed by combination the two smoothing methods of λ|μ and Laplacian. Third, feature points are detected by local surface differential geometry properties, and feature edges are extracted according to a selective mechanism, so an initial, rough segmentation is provided based on edge information. And then, the initial edge-based segmentation is enhanced by region-based segmentation method. How to estimate the differential geometry properties robustly, and how to detect feature points and feature edges and so on are studied in the paper. Range images acquired from Forbidden City of China are used to test the segmentation strategy, and results prove its efficiency and robustness.

Date Published: 28 October 2006
PDF: 8 pages
Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64191K (28 October 2006); doi: 10.1117/12.713254

Published in SPIE Proceedings Vol. 6419:
Geoinformatics 2006: Remotely Sensed Data and Information
Liangpei Zhang; Xiaoling Chen, Editor(s)