In previous research, three main approaches have been employed to solve the skeleton extraction problem: medial axis transform (MAT), generalized potential field and decomposition-based methods. These three approaches have been formulated using three different concepts, namely surface variation, inside energy distribution, and the connectivity of parts. By combining the above mentioned concepts, this paper creates a concise structure to represent the control skeleton of an arbitrary object.First, an algorithm is proposed to detect the end, connection and joint points of an arbitrary 3D object. These three points comprise the skeleton, and are the most important to consider when describing it. In order to maintain the stability of the point extraction algorithm, a prong-feature detection technique and a level iso-surfaces function-based on the repulsive force field was employed. A neighborhood relationship inherited from the surface able to describe the connection relationship of these positions was then defined. Based on this relationship, the skeleton was finally constructed and named domain connected graph (DCG). The DCG not only preserves the topology information of a 3D object, but is also less sensitive than MAT to the perturbation of shapes. Moreover, from the results of complicated 3D models, consisting of thousands of polygons, it is evident that the DCG conforms to human perception.