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Erschienen in:
2002 | OriginalPaper | Buchkapitel
Mining of Topographic Feature from Heterogeneous Imagery and Its Application to Lunar Craters
verfasst von : Rie Honda, Yuichi Iijima, Osamu Konishi
Erschienen in: Progress in Discovery Science
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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In this study, a crater detection system for a large-scale image database is proposed. The original images are grouped according to spatial frequency patterns and both optimized parameter sets and noise reduction techniques used to identify candidate craters. False candidates are excluded using a self-organizing map (SOM) approach. The results show that despite the fact that a accurate classification is achievable using the proposed technique, future improvements in detection process of the system are needed.