From Crater to Graph: Manual and Automated Crater Counting Techniques
Abstract
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.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2005
- Bibcode:
- 2005AGUFM.P23A0185P
- Keywords:
-
- 5420 Impact phenomena;
- cratering (6022;
- 8136);
- 5464 Remote sensing;
- 5494 Instruments and techniques;
- 6225 Mars