Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
This paper presents the automated detection of impact craters on large regions of Mercury. The processing sequence is composed by three main phases: the first consists on creating the image mosaics of the large areas of interest, the second by finding crater candidates on these mosaics, and finally by extracting a set of features that are used in the classification by SVM-Support Vector Machine in the third phase. The detections are performed on images acquired by the MDIS-NAC camera of MESSENGER probe covering three large basins on Mercury (Rachmaninoff, Mozart and Raditladi). © Springer International Publishing Switzerland 2015.
Year of publication: 2015