Wavelet-based Reflection Symmetry Detection via Textural and Color Histograms

Mohamed Elawady 1 Christophe Ducottet 1 Olivier Alata 1 Cecile Barat 1 Philippe Colantoni 2
1 LHC - Laboratoire Hubert Curien [Saint Etienne]
2 C2RMF - Centre de recherche et de restauration des musées de France
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.
Type de document :
Communication dans un congrès
ICCV 2017, IEEE International Conference on Computer Vision Workshop Detecting Symmetry in the Wild, Oct 2017, Venice, Italy. IEEE International Conference on Computer Vision Workshop Detecting Symmetry in the Wild. 〈10.1109/ICCVW.2017.202〉
Liste complète des métadonnées

Littérature citée [29 références]  Voir  Masquer  Télécharger
https://hal-ujm.archives-ouvertes.fr/ujm-01637175
Contributeur : Christophe Ducottet <>
Soumis le : lundi 20 novembre 2017 - 13:12:52
Dernière modification le : vendredi 14 septembre 2018 - 09:56:02
Document(s) archivé(s) le : mercredi 21 février 2018 - 12:22:41

Fichier

iccv-paper-wavelet.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

UNIV-ST-ETIENNE | IOGS | PARISTECH | UNIV-PARIS-SACLAY

Citation

Mohamed Elawady, Christophe Ducottet, Olivier Alata, Cecile Barat, Philippe Colantoni. Wavelet-based Reflection Symmetry Detection via Textural and Color Histograms. ICCV 2017, IEEE International Conference on Computer Vision Workshop Detecting Symmetry in the Wild, Oct 2017, Venice, Italy. IEEE International Conference on Computer Vision Workshop Detecting Symmetry in the Wild. 〈10.1109/ICCVW.2017.202〉. 〈ujm-01637175〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

54

Téléchargements de fichiers

47

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD