Abstract
We propose a randomized method for the detection of symmetry in planar polygons without assuming the predetermination of the centroids of the objects. Using a voting process, which is the main concept of the Hough transform in image processing, we transform the geometric computation for symmetry detection which is usually based on graph theory and combinatorial optimization, to the peak detection problem in a voting space in the context of the Hough transform.
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© 2000 Springer-Verlag Berlin Heidelberg
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Imiya, A., Ueno, T., Fermin, I. (2000). Planar Symmetry Detection by Random Sampling and Voting Process. In: Ferri, F.J., Iñesta, J.M., Amin, A., Pudil, P. (eds) Advances in Pattern Recognition. SSPR /SPR 2000. Lecture Notes in Computer Science, vol 1876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44522-6_36
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DOI: https://doi.org/10.1007/3-540-44522-6_36
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