Automated Detection of Sand Dunes on Mars

摘要

In this paper we show that the detection of dune fields on images of the surface of Mars, however varied they are, can be achieved through the application of an automated methodology. The procedure is based on the extraction of local information from images after they are organized according to a regular grid which defines cells, in turn aggregated into larger regions (blocks) that constitute the detection units. A set of gradient features is extracted and tested with Boosting and Support Vector Machine classifiers. A detection rate of 98.7% was obtained for a 5-fold cross validation on a set of images captured by the Mars Orbital Camera on board the Mars Global Surveyor probe.