Reflection Symmetry Detection in Images: Application to Photography Analysis

Citation

Elsayed Elawady M (2019) Reflection Symmetry Detection in Images: Application to Photography Analysis. Doctor of Philosophy. Université de Lyon. https://hal.archives-ouvertes.fr/tel-02305545/

Abstract
Symmetry is a fundamental principle of the visual perception to feel the equally distributed weights within foreground objects inside an image. It is used as a significant visual feature through various computer vision applications (i.e. object detection and segmentation), plus as an important composition measure in art domain (i.e. aesthetic analysis). The development of symmetry detection has been improved rapidly since last century. In this thesis, we mainly aim to propose new approaches to detect reflection symmetry inside real-world images in a global scale. In particular, our main contributions concern feature extraction and global representation of symmetry axes. First, we propose a novel approach that detects global salient edges inside an image using Log-Gabor filter banks, and defines symmetry oriented similarity through textural and color around these edges. This method wins a recent symmetry competition worldwide in single and multiple cases. Second, we introduce a weighted kernel density estimator to represent linear and directional symmetrical candidates in a continuous way, then propose a joint Gaussian-vonMises distance inside the mean-shift algorithm, to select the relevant symmetry axis candidates along side with their symmetrical densities. In addition, we introduce a new challenging dataset of single symmetry axes inside artistic photographies extracted from the large-scale Aesthetic Visual Analysis (AVA) dataset. The proposed contributions obtain superior results against state-of-art algorithms among all public datasets, especially multiple cases in a global scale. We conclude that the spatial and context information of each candidate axis inside an image can be used as a local or global symmetry measure for further image analysis and scene understanding purposes.

Keywords
Mean-shift; Image analysis; Detection; Reflection Symmetry; Symmetry axis; Symmetry measure; log-Gabor wavelets; linear directional analysis; kernel density estimation