SEGMENTATION OF RANGE IMAGES

The analyses of three-dimensional (3D) scenes from range data need the segmentation of 3D surfaces into planar patches and quadratic surface regions. In this paper the concept of the Digital Neighbourhood Planes introduced earlier (Pattern Recognition Lett. 11(3), 215-223 (1990)) for 3D binary data is suitably extended for the segmentation of range images. For range images the local neighbourhood of every point is virtually exploded (to 3 x 3 x 5, 3 x 3 x 7, etc.) and Neighbourhood Plane Set (NPS) values, indicative of the orientation of the surface normal at every range pixel, are computed. Subsequently a region growing technique is adopted to cluster points based on the NPS values which, with suitable post-processing, result in the final segments. The algorithm is simple and computationally efficient as it uses set-theoretic operations only. The algorithm is illustrated with the help of several examples. For most of them it produces good segmentation results. Finally, the algorithm has enough potential for parallelization which can be explored in the future.