Automated crater detection and counting using the hough transform
|dc.identifier.citation||Galloway, M. and Benedix, G. and Bland, P. and Paxman, J. and Towner, M. and Tan, T. 2014. Automated crater detection and counting using the hough transform, in Proceedings of the 2014 IEEE International Conference on Image Processing (ICIP), Oct 27-30 2014, pp. 1579-1583. Paris: Institute of Electrical and Electronics Engineers Inc..|
© 2014 IEEE. A manual process for detecting and counting craters on the surface of a planetary body becomes impractical when attempting to survey a large surface area. Similarly, existing automated methods that are effective for specific areas of focus are also impractical for a large data set. We report on the work completed so far in developing a crater detection system to automatically detect craters down to sub-km sizes, across a large portion of a planetary surface. Specifically, we assess the performance of a Hough Transform (HT) for the application and in particular the influence of its preprocessing edge detection phase. Tests are performed on high resolution images of the Martian surface, anticipating a large scale crater counting application for crater chronology on the surface of Mars.
|dc.publisher||Institute of Electrical and Electronics Engineers Inc.|
|dc.title||Automated crater detection and counting using the hough transform|
|dcterms.source.title||2014 IEEE International Conference on Image Processing, ICIP 2014|
|dcterms.source.series||2014 IEEE International Conference on Image Processing, ICIP 2014|
|curtin.department||Department of Applied Geology|
|curtin.accessStatus||Fulltext not available|
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