This paper deals with the problem of segmenting a 3D scene obtained by range imaging. It assumes scenes of arbitrary complexity in which the objects to be recognized are newly added or removed and investigates how the methods of change detection and image difference used in classical image processing can be used in range imaging. In a first step, we consider the case of ideal range images and conduct an analysis of segmentation by range image difference that shows the direct applicability of this principle. In a second step, we consider the case of the wide class of range sensors that suffer from shadowing effects which leads to missing data in the range image. An interpretation of this ambiguity in difference calculation and means to remove it will be given. Additional rules for the practical segmentation of 3D scenes by range image change detection are described. The presented methods lead to the possibility to segment a scene by isolating newly added or removed objects. They are tested using range images from two distinct range imagers of the light stripping type. Results indicate the success of this approach and the practical possibility to use it in the frame of an assembly task.