Abstract
In the last three years NASA and some other Space Agencies have draw some interest to date Mars surface, mainly because the relationship between its geological age and the probable presence of water beneath it. One way to do this is by classifying craters on the surface attending to their degree of erosion. The naïve way to solve this problem would let a group of experts analyze the images of the surface and let them mark and classify the craters. Unfortunately, this solution is unfeasible because the number of images is huge in comparison with the human resources any group can afford. Different solutions have been tried [1], [2] over this period of time. This paper offers an autonomous Computer Vision System to detect the craters, and classify them.
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Flores-Méndez, A. (2003). Crater Marking and Classification Using Computer Vision. In: Sanfeliu, A., Ruiz-Shulcloper, J. (eds) Progress in Pattern Recognition, Speech and Image Analysis. CIARP 2003. Lecture Notes in Computer Science, vol 2905. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24586-5_9
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DOI: https://doi.org/10.1007/978-3-540-24586-5_9
Publisher Name: Springer, Berlin, Heidelberg
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