This work proposes a new method for detection of craters from digital topography images. The results are: (1) a framework for development and basic evaluation of crater detection algorithms (CDAs), which includes a measurement definition for distances between craters (in longitude-latitude-diameter space); (2) a catalogue for evaluation of CDAs, which consists of 57633 craters catalogued without usage of CDAs, including methods for evaluation of consistency and for integration of catalogues; (3) a method for crater detection using edge detection and gradient, modified Hough transform, morphometry measurements and analysis of topography and parameter space of Hough transform, slip-tuning, and calibration; (4) methodology for advanced evaluation of CDAs using topography and image datasets, including a method for registration of craters between different catalogues based on context, interactive evaluation of crater-candidates and registration in catalogue; (5) an improvement of crater detection utilizing a Crater Shape-based interpolation method that proved to be efficient for the detection of very small craters from the topographies of Mars and the Moon; and (6) an additional improvement of crater detection using support vector machines, which considerably decreases false detections. The accompanying results are the most complete publically available catalogues for Mars and the Moon, with 132843 and 64215 craters, respectively, and applicability for: Phobos’ topography (catalogue with 1102 craters), evaluation of laboratory craters, topography reconstructed from Lunar optical images, and topographies of Venus (catalogue with 345 craters) and Earth (catalogue with 24 craters).