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Proceedings Paper

Automated detection and classification for craters based on geometric matching
Author(s): Jian-qing Chen; Ping-yuan Cui; Hui-tao Cui
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Paper Abstract

Crater detection and classification are critical elements for planetary mission preparations and landing site selection. This paper presents a methodology for the automated detection and matching of craters on images of planetary surface such as Moon, Mars and asteroids. For craters usually are bowl shaped depression, craters can be figured as circles or circular arc during landing phase. Based on the hypothesis that detected crater edges is related to craters in a template by translation, rotation and scaling, the proposed matching method use circles to fitting craters edge, and align circular arc edges from the image of the target body with circular features contained in a model. The approach includes edge detection, edge grouping, reference point detection and geometric circle model matching. Finally we simulate planetary surface to test the reasonableness and effectiveness of the proposed method.

Paper Details

Date Published: 15 August 2011
PDF: 6 pages
Proc. SPIE 8196, International Symposium on Photoelectronic Detection and Imaging 2011: Space Exploration Technologies and Applications, 81961T (15 August 2011); doi: 10.1117/12.901020
Show Author Affiliations
Jian-qing Chen, Harbin Institute of Technology (China)
Ping-yuan Cui, Beijing Institute of Technology (China)
Hui-tao Cui, Harbin Institute of Technology (China)


Published in SPIE Proceedings Vol. 8196:
International Symposium on Photoelectronic Detection and Imaging 2011: Space Exploration Technologies and Applications
John C. Zarnecki; Carl A. Nardell; Rong Shu; Jianfeng Yang; Yunhua Zhang, Editor(s)

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