1 March 1992 Contribution of edges and regions to range image segmentation
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Most of the segmentation algorithms of range images are based upon either a region approach or an edge approach. While the region growing methods are poor in delimiting the region boundaries, the edges do not give information about the different surfaces and are not connected. But these two approaches can collaborate because they give complementary information about the scene. In the proposed method we first extract edges from the image. Two kinds of edges are considered: occlusion edges or signal discontinuity and roof edges or orientation discontinuities. The edges are completed by a concurrent step and roof edges closing method in order to form initial closed regions by connected components labeling. Then begins an iterative region correcting process. At each iteration we fit a least squares bivariate polynomial to every region. Then each boundary point is examined to see if it is better approximated by its region or by a neighboring region. But the regions are not allowed to overpass initial edge points considered as confident surface boundaries. This process converges after few iterations and produces a better correspondence between the shapes of the regions and the surfaces of the objects. Results are shown for real range images.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andre Davignon, Andre Davignon, } "Contribution of edges and regions to range image segmentation", Proc. SPIE 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics, (1 March 1992); doi: 10.1117/12.58575; https://doi.org/10.1117/12.58575


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