A hybrid to range image detection

An approach to the problem of range image segmentation is described. It is a hybrid of region- and edge-based approaches. It is assumed that the range image of an object, which may be constructed of both curved and planar surfaces, is divided into surface primitives which are homogeneous in their intrinsic differential geometric properties and do not contain discontinuities in either depth or surface orientation. The method is based on the computation of the Gaussian and mean curvatures from which a curvature sign map is computed. Two initial edge-based segmentations are also computed from the partial derivatives and depth values. One detects jump edges while the other highlights roof edges. The three image maps are then combined to produce the final range image segmentation. Experimental results for both synthetic and real range data of polyhedral and curved objects have proved the usefulness of the approach. Results for the real data are given