Bilateral symmetry detection based on scale invariant structure feature

Symmetry is a salient visual pattern in images. Symmetrical structure attracts human eye more than other regions. Therefore, detecting symmetry in an image is one of the crucial tasks in pattern recognition and computer vision research. Sparse key point based symmetry detection methods have been proposed which are fast and robust to noise showing superior detection performance. However, such local appearance-based methods have difficulties in capturing structure based patterns mostly supported by edges and contours. In this paper, we propose a scale invariant structure feature which describes points on extremum curvature along edges. We propose to use a histogram of curvature responses at respective scale space for description. Experimental evaluation on public shape dataset and real world images show that our structure feature works better in detecting visually salient structure based symmetry patterns.