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Automated Crater Detection, A New Tool for Mars Cartography and Chronology.

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Title: Automated Crater Detection, A New Tool for Mars Cartography and Chronology.
Authors: Jung Rack Kim1 jkim@ge.ucl.ac.uk, Muller, Jan-Peter1, van Gasselt, Stephan2, Morley, Jeremy G.1, Neukum, Gerhard2
Source: Photogrammetric Engineering & Remote Sensing. Oct2005, Vol. 71 Issue 10, p1205-1217. 13p.
Subjects: Lunar craters, Algorithms, Map projection, Geomorphology, Cartography, Detectors
Abstract: An automated crater detection algorithm is presented which exploits image data. The algorithm is briefly described and its application demonstrated on a variety of different Martian geomorphological areas and sensors (Viking Orbiter Camera, Mars Orbiter Camera (MOC), Mars Orbiter Laser Altimeter (MOLA), and High Resolution Stereo Camera (HRSC)). We show assessment results through both an inter-comparison of automated crater locations with those from the manually-derived Mars Crater Consortium (MCC) catalogue and the manually-derived craters. The detection algorithm attains an accuracy of 70 to 90 percent and a quality factor of 60 to 80 percent depending on target sensor type and geomorphology. We also present crater detection results derived from HRSC images onboard the ESA Mars Express on a comparison between manually-determined Size-Frequency Distributions (SFDs) and those derived fully automatically. The approach described appears to offer great potential for chronological research, geomatic and geological analysis and for other purposes of extra-terrestrial planetary surface mapping. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:An automated crater detection algorithm is presented which exploits image data. The algorithm is briefly described and its application demonstrated on a variety of different Martian geomorphological areas and sensors (Viking Orbiter Camera, Mars Orbiter Camera (MOC), Mars Orbiter Laser Altimeter (MOLA), and High Resolution Stereo Camera (HRSC)). We show assessment results through both an inter-comparison of automated crater locations with those from the manually-derived Mars Crater Consortium (MCC) catalogue and the manually-derived craters. The detection algorithm attains an accuracy of 70 to 90 percent and a quality factor of 60 to 80 percent depending on target sensor type and geomorphology. We also present crater detection results derived from HRSC images onboard the ESA Mars Express on a comparison between manually-determined Size-Frequency Distributions (SFDs) and those derived fully automatically. The approach described appears to offer great potential for chronological research, geomatic and geological analysis and for other purposes of extra-terrestrial planetary surface mapping. [ABSTRACT FROM AUTHOR]
ISSN:00991112
DOI:10.14358/PERS.71.10.1205