Last update: Feb. 10, 2004
Publications by Herb Yang et al. on shape symmetry elicitation :
BibTeX references.
T. Grigorishin and Y.H. Yang
Pattern Analysis and Applications, Vol. 1, 1998, pp. 163-177.
Skeleton representation of an object is a powerful shape descriptor that captures both boundary and region information of the object. The skeleton of a shape is a representation composed of idealized thin lines that preserve the connectivity or topology of the original shape. Although the literature contains a large number of skeletonization algorithms, many open problems remain. In this paper, we present a new skeletonization approach that relies on the Electrostatic Field Theory (EFT). Many problems associated with existing skeletonization algorithms are solved using the proposed approach. In particular, connectivity, thinness, and other desirable features of a skeleton are guaranteed. It also captures notions of corner detection, multiple scale, thinning, and skeletonization all within one unified framework. The performance of the proposed EFT-based algorithm is studied extensively. Using the Hausdorf distance measure, the noise sensitivity of the algorithm is compared to two existiing skeletonization techniques.
Gamal Abdel-Hamid, Yee-Hong Yang
Dept. of Comp. Science, University of Saskatchewan, Tech. Report, Dec. 1994.
Also, in shorter version under:
Proc. IEEE International Conference on Image Processing,
Nov. 13-16, 1994, Austin, Texas, Vol. I, pp. 949-953.
Skeleton representation of an object is believed to be a powerful representation that captures both boundary and region information of the object. The skeleton of a shape is a representation composed of idealized thin lines that preserve the connectivity or topology of the original shape. Although the literature contains a large number of skeletonization algorithms, many open problems remain. In this paper, a new skeletonization approach that relies on the Electrostatic Field Theory (EFT) is proposed. Many problems associated with existing skeletonization algorithms are solved using the proposed approach. In particular, connectivity, thinness, and other desirable features of a skeleton are guaranteed. Furthermore, the electrostatic field-based approach captures notions of corner detection, multiple scale, thinning, and skeletonization all within one unified framework. Experimental results are very encouraging and are used to illustrate the potential of the proposed approach.
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2004.
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