Global Bilateral Symmetry Detection Using Multiscale Mirror Histograms

Citation

Elawady M, Barat C, Ducottet C & Colantoni P (2016) Global Bilateral Symmetry Detection Using Multiscale Mirror Histograms. In: Blanc-Talon J, Distante C, Philips W, Popescu D & Scheunders P (eds.) Advanced Concepts for Intelligent Vision Systems. ACIVS 2016. Lecture Notes in Computer Science, 10016. ACIVS 2016: International Conference on Advanced Concepts for Intelligent Vision Systems, Leece, Italy, 24.10.2016-27.10.2016. Cham, Switzerland: Springer International Publishing, pp. 14-24. https://doi.org/10.1007/978-3-319-48680-2_2

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.

Keywords
Symmetry detection; Reflection symmetry; Edge features; Pairwise similarity; Symmetry histogram

• Accepted manuscript