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- W1604920271 abstract "Symmetry is an important feature in vision. Several detectors or transforms have been proposed. In this paper we concentrate on a measure of symmetry. Given a transform S, the kernel SK of a pattern is defined as the maximal included symmetric sub-set of this pattern. The maximum being taken over all directions, the problem arises to know which center to use. Then the optimal direction triggers the shift problem too. We prove that, in any direction, the optimal axis corresponds to the maximal correlation of a pattern with its flipped version. That leads to an efficient algorithm. As for the measure we compute a modified difference between respective surfaces of a pattern and its kernel. A series of experiments supports actual algorithm validation.KeywordsBilateral SymmetrySymmetric PatternSymmetric VersionMorphological ErosionPattern Recognition LetterThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
- W1604920271 created "2016-06-24" @default.
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- W1604920271 date "2005-01-01" @default.
- W1604920271 modified "2023-10-14" @default.
- W1604920271 title "The S-Kernel and a Symmetry Measure Based on Correlation" @default.
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- W1604920271 doi "https://doi.org/10.1007/11499145_21" @default.
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