Detecting Symmetry in Grey Level Images: The Global Optimization Approach

  • Authors:
  • Nahum Kiryati;Yossi Gofman

  • Affiliations:
  • Department of Electrical Engineering, Technion—Israel Institute of Technology, Haifa 32000, Israel;Department of Electrical Engineering, Technion—Israel Institute of Technology, Haifa 32000, Israel

  • Venue:
  • International Journal of Computer Vision
  • Year:
  • 1998

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Abstract

The detection of significant local reflectional symmetry in greylevel images is considered. Prior segmentation is not assumed, and it isintended that the results could be used for guiding visual attention and forproviding side information to segmentation algorithms. A local measure ofreflectional symmetry that transforms the symmetry detection problem to aglobal optimization problem is defined. Reflectional symmetry detectionbecomes equivalent to finding the global maximum of a complicatedmultimodal function parameterized by the location of the center of thesupporting region, its size, and the orientation of the symmetry axis.Unlike previous approaches, time consuming exhaustive search is avoided. Aglobal optimization algorithm for solving the problem is presented. It isrelated to genetic algorithms and to adaptive random search techniques. The efficiency of the suggested algorithm is experimentally demonstrated. Just one thousand evaluations of the local symmetry measure are typicallyneeded in order to locate the dominant symmetry in natural test images.