Computer Science – Artificial Intelligence
Scientific paper
Dec 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005agufm.p23a0185p&link_type=abstract
American Geophysical Union, Fall Meeting 2005, abstract #P23A-0185
Computer Science
Artificial Intelligence
5420 Impact Phenomena, Cratering (6022, 8136), 5464 Remote Sensing, 5494 Instruments And Techniques, 6225 Mars
Scientific paper
Impact craters are some of the most abundant, and most interesting features on Mars. They hold a wealth of information about Martian geology, providing clues to the relative age, local composition and erosional history of the surface. A great deal of effort has been expended to count and understand the nature of planetary crater populations (Hartman and Neukum, 2001). Highly trained experts have developed personal methods for conducting manual crater surveys. In addition, several efforts are underway to automate this process in order to keep up with the rapid increase in planetary surface image data. These efforts make use of a variety of methods, including the direct application of traditional image processing algorithms such as the Hough transform, and recent developments in genetic programming, an artificial intelligence-based technique, in which manual crater surveys are used as examples to `grow' or `evolve' crater counting algorithms. (Plesko, C. S. et al., LPSC 2005, Kim, J. R. et al., LPSC 2001, Michael, G. G. P&SS 2003, Earl, J. et al, LPSC 2005) In this study we examine automated crater counting techniques, and compare them with traditional manual techniques on MOC imagery, and demonstrate capabilities for the analysis of multi-spectral and HRSC Digital Terrain Model data as well. Techniques are compared and discussed to define and develop a robust automated crater detection strategy.
Asphaug Erik
Brumby Steven P.
Foing Bernard H.
Gerhard Neukum
Plesko Catherine S.
No associations
LandOfFree
From Crater to Graph: Manual and Automated Crater Counting Techniques does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with From Crater to Graph: Manual and Automated Crater Counting Techniques, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and From Crater to Graph: Manual and Automated Crater Counting Techniques will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-749076