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An Acceleration Method for Symmetry Detection using Edge Segmentation
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 Title & Authors
An Acceleration Method for Symmetry Detection using Edge Segmentation
Won, Bo Whan; Koo, Ja Young;
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Symmetry is easily found in animals and plants as well as in artificial structures. It is useful not only for human cognitive process but also for image understanding by computer. Application areas include face detection and recognition, indexing of image database, image segmentation and detection, and analysis of medical images. The method used in this paper extracts edges, and the perpendicular bisector of any pair of selected edge points is considered to be a candidate axis of symmetry. The coefficients of the perpendicular bisectors are accumulated in the coefficient space. Axis of symmetry is determined to be the line for which the histogram has maximum value. This method shows good results, but the usefulness of the method is restricted because the amount of computation increases proportional to the square of the number of edges. In this paper, an acceleration method is proposed which performs times faster than the original one. Experiment on 20 test images shows that the proposed method using level-3 image segmentation performs 63.9 times faster than the original method.
symmetry detection;reflectional symmetry;coefficient space histogram;image segmentation;acceleration method;
 Cited by
Circle Detection Using Its Maximal Symmetry Property,;

한국컴퓨터정보학회논문지, 2016. vol.21. 6, pp.21-28 crossref(new window)
Y. Liu et al., "Computational symmetry in computer vision and computer graphics," Foundations and Trends in Computer Graphics and Vision, vol. 5, pp. 1-195, 2010.

M.J. Atallah, "On Symmetry Detection," IEEE Trans. Computers, vol. 34, no. 7, pp. 663-666, July 1985.

S. Lee and Y. Liu, "Curved glide-reflection symmetry detection," IEEE Trans. PAMI, vol. 34, no. 2,pp. 266-278, 2012. crossref(new window)

V. Patraucean and R. G. von Gioi. "Detection of mirror symmetric image patches." CVPR workshop on Symmetry Detection from Real World Images, pp. 211-216, 2013

H. Akbar et al. "Bilateral Symmetry Detection on the Basis of Scale Invariant Feature Transform." PLoS ONE 9(8), 2014.

V.S.N. Prasad and B. Yegnanarayana, "Finding Axes of Symmetry from Potential Fields," IEEE Trans. Image Processing, vol. 13, no. 12, pp. 1559-1566, Dec. 2004. crossref(new window)

S. Mitra et al., "Understanding the role of facial asymmetry in human face identification." Statistics and Computing vol. 17, pp.57-70. 2007. crossref(new window)

A.K. Singh and G.C. Nandi. "Face recognition using facial symmetry." Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology (CCSEIT '12). ACM, New York, NY, USA, pp. 550-554. 2012.

B.H. Won, J.Y. Koo, "Rotated Face Detection Using Symmetry Detection," Journal of The Korea Society of Computer and Information, Vol 16, No 1, pp. 63-70, January 2011. crossref(new window)

D. Sharvit et al. (1998) "Symmetry-based indexing of image databases." Proc. IEEE Workshop on Content-Based Access of Image and Video Libraries. pp. 56-62. 1998.

W.H Li , A.M Zhang, and L. Kleeman "Real Time Detection and Segmentation of Reflectionally Symmetric Objects in Digital Images." IEEE/RSJ Int. Conf. on Intelligent Robots and Systems. pp. 4867-4873. 2006.

W.H Li , A.M Zhang, and L. Kleeman "Fast global reflectional symmetry detection for robotics grasping and visual tracking" Proceedings of Australasian Conference on Robotics and Automation., 2005.

S. A. Jayasuriya and A.W. C Liew, "Symmetry Plane Detection in Neuro Images based on Intensity Profile Analysis", International Symposium on Information Technology in Medicine and Education, pp.599-603, 2012.