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Université Jean Monnet – Saint-Etienne |  |
Conference papers
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.
Cited literature [21 references]
https://hal-ujm.archives-ouvertes.fr/ujm-01387193
Contributor : Christophe Ducottet <>
Submitted on : Wednesday, October 18, 2017 - 3:49:25 PM
Last modification on : Monday, January 13, 2020 - 5:46:06 PM
Contributor : Christophe Ducottet <>
Submitted on : Wednesday, October 18, 2017 - 3:49:25 PM
Last modification on : Monday, January 13, 2020 - 5:46:06 PM
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paper107-cor.pdf
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