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Université Jean Monnet – Saint-Etienne |  |
Conference papers
Wavelet-based Reflection Symmetry Detection via Textural and Color Histograms
Abstract : Symmetry is one of the significant visual properties inside an image plane, to identify the geometrically balanced structures through real-world objects. Existing symmetry detection methods rely on descriptors of the local image features and their neighborhood behavior, resulting incomplete symmetrical axis candidates to discover the mirror similarities on a global scale. In this paper, we propose a new reflection symmetry detection scheme, based on a reliable edge-based feature extraction using Log-Gabor filters , plus an efficient voting scheme parameterized by their corresponding textural and color neighborhood information. Experimental evaluation on four single-case and three multiple-case symmetry detection datasets validates the superior achievement of the proposed work to find global symmetries inside an image.
Cited literature [29 references]
https://hal-ujm.archives-ouvertes.fr/ujm-01637175
Contributor : Christophe Ducottet <>
Submitted on : Monday, November 20, 2017 - 1:12:52 PM
Last modification on : Monday, January 13, 2020 - 5:46:06 PM
Document(s) archivé(s) le : Wednesday, February 21, 2018 - 12:22:41 PM
Contributor : Christophe Ducottet <>
Submitted on : Monday, November 20, 2017 - 1:12:52 PM
Last modification on : Monday, January 13, 2020 - 5:46:06 PM
Document(s) archivé(s) le : Wednesday, February 21, 2018 - 12:22:41 PM
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iccv-paper-wavelet.pdf
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