Machine Detection of Martian Impact Craters From Digital Topography Data

Abstract

Research on automatic identification of impact craters on Mars and other planetary bodies has concentrated on detecting them from imagery data. We present a novel approach to crater detection that utilizes digital topography data instead of images. Craters are delineated by topographic curvature. Thresholding maps of curvature transforms topographic data into a binary image, from which craters are identified using a combination of segmentation and detection algorithms. We apply our method to a large and technically demanding test site and compare the results to the existing catalog of manually identified craters. Our algorithm finds many small craters not listed in the manual catalog, but it fails to detect heavily degraded craters. A detailed quality assessment of the algorithm is presented. The topography-based crater-detection algorithm offers a relatively simple and ready-to-use tool for identification and characterization of fresh impact craters with an adequate performance for the immediate application to Martian geomorphology