The robust extraction of feature areas on surface objects embedded in 3D, like circular shapes, is a challenging problem. Classical approaches generally rely on image processing and template matching on a 2D flat projection of the 3D object (for instance a high-resolution photograph). In this chapter, we propose two full 3D methods using curvature operators to extract these features. In the first approach, a tagging stage of regions of interest is performed over a 3D model of the object in order to extract the features. A single circular connected line is constructed, exclusively composed of edges of the initial mesh around each detected area. The second approach starts with the detection of pits. Then, “best fit circles” are found according to the rims of the circular shapes. We apply these approaches to the detection of craters on celestial bodies observed by space missions, here the asteroids Vesta and Lutetia.