Feature detection from local energy
Pattern Recognition Letters
Symmetry detection using gradient information
Pattern Recognition Letters
Modeling and Classifying Symmetries Using a Multiscale Opponent Color Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast reflectional symmetry detection using orientation histograms
Real-Time Imaging - Special issue on real-time defect detection
IEEE Transactions on Computers
Depicting procedural caustics in single images
ACM SIGGRAPH Asia 2008 papers
Testing for image symmetries: with application to confocal microscopy
IEEE Transactions on Information Theory
Connecting content to community in social media via image content, user tags and user communication
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Discovering multirelational structure in social media streams
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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Symmetry exists widely in the real world and plays a remarkable role in perception problems. The existing symmetry detection algorithms are mainly based on luminance or gradient information. Upon analyzing the relationship between symmetry and phase, based on phase congruency, we propose a phase-based symmetry detection (PSD) algorithm. PSD is calculated based on log Gabor wavelet. The symmetric points of objects are obtained by inspecting the phase information. The feasibility analysis, phase-based symmetry detection definition, and rationality demonstrations established the theoretic foundation for this algorithm. The experiments show that this algorithm can be applied directly to original images without segmentation-it is invariant to rotation, luminance and contrast-and it can detect several types of symmetries at the same time and it is compared with several other methods.