Abstract
We describe a technique for extracting vertices from range images of cluttered box-like objects. Edge detection is performed and an edge map is acquired. Extraction of vertices is carried out using the edge map and comprises two steps: Linear boundary detection in 3D and boundary grouping. In order to recover the four parameters of a 3D linear segment, we decompose the problem in two 2D subproblems, each recovering two line parameters. These subproblems are solved by means of the Hough Transform, constrained in this way so that accurate and efficient propagation of the edge points localization error is achieved. Pairs of orthogonal boundaries are grouped to form a vertex. The orthogonality of a boundary pair is determined by a simple statistical test. Our strategy comprises many advantages, the most important of which robustness, computational efficiency and accuracy, the combination of which is not to be found in existing approaches.
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Katsoulas, D. (2003). Robust Extraction of Vertices in Range Images by Constraining the Hough Transform. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_42
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DOI: https://doi.org/10.1007/978-3-540-44871-6_42
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