Self-Clustering Symmetry Detection

Bei HE, Guijin WANG, Chenbo SHI, Xuanwu YIN, Bo LIU, Xinggang LIN
2012 IEICE transactions on information and systems  
This paper presents a self-clustering algorithm to detect symmetry in images. We combine correlations of orientations, scales and descriptors as a triple feature vector to evaluate each feature pair while low confidence pairs are regarded as outliers and removed. Additionally, all confident pairs are preserved to extract potential symmetries since one feature point may be shared by different pairs. Further, each feature pair forms one cluster and is merged and split iteratively based on the
more » ... inuity in the Cartesian and concentration in the polar coordinates. Pseudo symmetric axes and outlier midpoints are eliminated during the process. Experiments demonstrate the robustness and accuracy of our algorithm visually and quantitatively.
doi:10.1587/transinf.e95.d.2359 fatcat:3lcfgo6ygbbovmhcyk5b75vwvu