Crater Detection on Mars

Background: Detecting craters in satellite images has many applications for planetary geologists, including providing an indicator of the age of the terrain and in registering images taken in different modalities. Craters are so numerous that automated methods can greatly increase the efficiency of this analysis.

Solution: The method developed in this project started with identifying candidate craters by locating circular features. A set of intensity, texture, shading, template, and boundary features were then extracted on each candidate to learn a model of a crater. This model was successfully used to distinguish craters from non-craters.

Alternative Applications: Many modern object detection algorithms start by proposing candidate regions, followed by a second stage to determine whether each region contains the desired object. By finding the candidate regions efficiently and with high recall, the second stage can provide the necessary precision to the algorithm. This combination makes for an efficient and accurate algorithm that is applicable for many types of objects.