TY - GEN
T1 - Sequence detection of planetary surface craters from DEM data
AU - Yu, Zhengshi
AU - Zhu, Shengying
AU - Cui, Pingyuan
PY - 2012
Y1 - 2012
N2 - The research on identification and recognition of impact craters on planetary surface is focused on how to detect them from background. A novel sequence algorithm is proposed to crater detection that utilizes DEM data instead of images. By investigating the features of ideal craters, several constraints can be developed to extract candidate crater edges from other topographies. Based on the fact that the shape of most craters is approximate to an ellipse, the Least Median Square Ellipse Fitting Method can be used to exclude pseudo-edges, and to reserve the real edges which contain the feature of the crater. The location, orientation and other physical parameters of the crater can be determined by fitting real edges to an ellipse based on Robust Least Square Method. Mathematical simulations are performed with the moon DEM data. The results show that the topography-based crater detection algorithm offers an effective method for identification and characterization of ellipse-like impact craters, and the accuracy is high enough.
AB - The research on identification and recognition of impact craters on planetary surface is focused on how to detect them from background. A novel sequence algorithm is proposed to crater detection that utilizes DEM data instead of images. By investigating the features of ideal craters, several constraints can be developed to extract candidate crater edges from other topographies. Based on the fact that the shape of most craters is approximate to an ellipse, the Least Median Square Ellipse Fitting Method can be used to exclude pseudo-edges, and to reserve the real edges which contain the feature of the crater. The location, orientation and other physical parameters of the crater can be determined by fitting real edges to an ellipse based on Robust Least Square Method. Mathematical simulations are performed with the moon DEM data. The results show that the topography-based crater detection algorithm offers an effective method for identification and characterization of ellipse-like impact craters, and the accuracy is high enough.
KW - Crater detection
KW - DEM
KW - Least Median Square Ellipse Fitting
KW - Robust Least Square Method
UR - http://www.scopus.com/inward/record.url?scp=84872295415&partnerID=8YFLogxK
U2 - 10.1109/WCICA.2012.6359383
DO - 10.1109/WCICA.2012.6359383
M3 - Conference contribution
AN - SCOPUS:84872295415
SN - 9781467313988
T3 - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
SP - 4775
EP - 4779
BT - WCICA 2012 - Proceedings of the 10th World Congress on Intelligent Control and Automation
T2 - 10th World Congress on Intelligent Control and Automation, WCICA 2012
Y2 - 6 July 2012 through 8 July 2012
ER -