Automatic Lunar Crater Detection Based on DEM Data Using a Max Curvature Detection Method

Lunar crater is crucial for estimating the age of the Moon and investigating the evolution of both the Moon and the solar system. However, the bottom of the crater is usually uneven, resulting in automatic detection difficult to obtain a complete impact crater. This letter proposes an automated lunar crater detection algorithm (CDA), which is robust to the complicated variations of impact craters, based on digital elevation model (DEM) data. The lowest points on the DEM were extracted as the potential centers of craters. The rim of craters was first detected by a max curvature detection method and then completed by the watershed algorithm. The algorithm was applied to the lunar mare and highland and compared with the crater database obtained by Robbins. The results show that the algorithm could detect numerous small and complicated types of craters. In the lunar highlands, the algorithm detected 74% of documented impact craters, the newly detected impact craters accounted for 82.79%, and the overall reliability exceeded 81%. In the lunar mare, the algorithm identified over 50% of established craters, more than 66% of detected craters were new, and the overall reliability was greater than 56%. The algorithm calculated the structural attributes and obtained the true rim. Only the DEM data are required, and the algorithm is portable to other planets, such as Mars.