Because of the availability of explicit 3D information, the use of range data has become quite popular in computer vision. One of the common methods for range data acquisition is based on coded light. An advantage of this method is that it yields not only a range image of a scene, but also a greylevel image that is in registration with the range image. Thus, information from the greylevel and range image can be easily combined. On the other hand, the coded light approach suffers from the existence of shadow areas, where no range data can be measured. That is, it gives only an incomplete range image, in general. In this paper, we present a new approach to the interpretation of edges in range images of polyhedra. First, we integrate the edges extracted from the greylevel and range image of a scene. Then, the edges are classified into one of the types jump, convex, concave, or non-geometric. While jump, convex, and concave edges correspond to real edges, the non-geometric edges, which are caused by shadow, can be removed. Such a classification of physical edges together with the elimination of shadow edges potentially improves any subsequent object recognition step.