Paper
15 August 2011 Automated detection and classification for craters based on geometric matching
Jian-qing Chen, Ping-yuan Cui, Hui-tao Cui
Author Affiliations +
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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jian-qing Chen, Ping-yuan Cui, and Hui-tao Cui "Automated detection and classification for craters based on geometric matching", Proc. SPIE 8196, International Symposium on Photoelectronic Detection and Imaging 2011: Space Exploration Technologies and Applications, 81961T (15 August 2011); https://doi.org/10.1117/12.901020
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Data modeling

Edge detection

Asteroids

Detection and tracking algorithms

Space operations

Aerospace engineering

Feature extraction

Back to Top