Global Bilateral Symmetry Detection Using Multiscale Mirror Histograms

Abstract : In recent years, there has been renewed interest in bilateral symmetry detection in images. It consists in detecting the main bilateral symmetry axis inside artificial or natural images. State-of-the-art methods combine feature point detection, pairwise comparison and voting in Hough-like space. In spite of their good performance, they fail to give reliable results over challenging real-world and artistic images. In this paper, we propose a novel symmetry detection method using multi-scale edge features combined with local orientation histograms. An experimental evaluation is conducted on public datasets plus a new aesthetic-oriented dataset. The results show that our approach outperforms all other concurrent methods.
Type de document :
Communication dans un congrès
Springer. 17th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS 2016) , Oct 2016, Lecce, Italy. Lecture Notes in Computer Science 10016, pp.14 - 24, 2016, Advanced Concepts for Intelligent Vision Systems. 〈10.1007/978-3-319-48680-2_2〉
Liste complète des métadonnées

Littérature citée [21 références]  Voir  Masquer  Télécharger

https://hal-ujm.archives-ouvertes.fr/ujm-01387193
Contributeur : Christophe Ducottet <>
Soumis le : mercredi 18 octobre 2017 - 15:49:25
Dernière modification le : jeudi 26 juillet 2018 - 01:10:31

Fichier

paper107-cor.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Citation

Mohamed Elawady, Cécile Barat, Christophe Ducottet, Philippe Colantoni, Cecile Barat. Global Bilateral Symmetry Detection Using Multiscale Mirror Histograms. Springer. 17th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS 2016) , Oct 2016, Lecce, Italy. Lecture Notes in Computer Science 10016, pp.14 - 24, 2016, Advanced Concepts for Intelligent Vision Systems. 〈10.1007/978-3-319-48680-2_2〉. 〈ujm-01387193v2〉

Partager

Métriques

Consultations de la notice

39

Téléchargements de fichiers

89