DocumentCode :
3327030
Title :
Automatic recognition of Martian craters based on MOLA-derived digital topography
Author :
Shuanggen Jin ; Tengyu Zhang
Author_Institution :
Shanghai Astron. Obs., Shanghai, China
fYear :
2013
fDate :
23-24 Dec. 2013
Firstpage :
1010
Lastpage :
1013
Abstract :
The recognition of impact craters can provide information on impact craters´ history and Martian evolution processes as well as for Martian rover landing site. Most previous studies about machine detection of impact craters on Mars are based on imagery data, however, it has large uncertainty in image processing. In this study, we present a novel approach for automatic recognition of impact craters based on the Mars Orbiter Laser Altimeter (MOLA)-derived digital topography data. Topographic curvature, which delineates impact crater on Digital Elevation Model (DEM), can be deduced from topography data. The thresholding map of curvature is transformed into a binary map, from which we can detect impact craters by combination of segmentation and flooding algorithms. More impact craters on Mars with confirmation algorithm can be effectively distinguished truly, which are added the existing catalog of manually identified Martian craters. It will be more useful for the study on impact craters´ history and Martian evolution processes as well as Martian rover landing navigation.
Keywords :
Mars; astronomical image processing; image recognition; meteorite craters; planetary rovers; planetary surfaces; satellite navigation; DEM; MOLA-derived digital topography; Mars Orbiter Laser Altimeter; Martian craters; Martian evolution process; Martian rover landing navigation; Martian rover landing site; automatic recognition; binary map; digital elevation model; flooding algorithms; image processing; imagery data; impact crater recognition; machine detection; segmentation; topographic curvature; Automation; Catalogs; Mars; Optical imaging; Optical sensors; Surface morphology; Surface topography; Automatic recognition; DEM; HRSC; Martian craters;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement, Sensor Network and Automation (IMSNA), 2013 2nd International Symposium on
Conference_Location :
Toronto, ON
Type :
conf
DOI :
10.1109/IMSNA.2013.6743452
Filename :
6743452
Link To Document :
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