We present a box depalletizing system based on images acquired with a time of flight laser sensor mounted on the hand of the robot. Scanning the upper layer of the pallet yields a 2.5D image to which edge detection and robust line fitting are applied to extract 3D vertices. This vertex information is used as an input for a model based object recognition system. Model vertices are matched to scene vertices and object location hypothesis are formed. These hypotheses are verified or rejected using a two-step verification process. Due to the fact that we use edges to extract vertices, rather than surfaces, we are able to detect target objects, in both cluttered and ordered configurations. Our experiments with different configurations of cardboard boxes and paper tissue packets demonstrate the validity of our approach. The main advantages of our system are it's versatility, simplicity, efficiency and robustness.