A novel automatic method is developed for the detection of features in planetary images. Although many automatic feature extraction methods have been proposed for for remote sensing images of the Earth, these methods are typically unfeasible for planetary data that generally present low contrast and uneven illumination characteristics. Here, a novel technique for crater detection, based on a marked point process, is proposed. The main idea behind marked point processes is to model objects within a stochastic framework: They provide a powerful and methodologically rigorous framework to efficiently map and detect objects and structures in an image with an excellent robustness to noise. These methods are new and promising: They represent the last frontier of the stochastic image modeling. They have been used in different areas of the terrestrial remote sensing, but have not been applied to planetary image analysis yet. The proposed method for crater detection has many other areas applications. One such application area is image registration by matching the extracted features.