Shape Recognition Using Skeleton Image Based on Mathematical Morphology


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 3, No. 4, pp. 883-898, Jul. 1996
10.3745/KIPSTE.1996.3.4.883,   PDF Download:

Abstract

In this paper, we propose an improved method to recognize the shape for enhancing the quality of the pattern recognition system by compressing the source images. In the proposed method, we reduced the data amount by skeletonizing the source images using mathematical morphology, and then matched patterns after accomplishing the translation and scale normalization, and rotation invariance on the transformed images. Through the scale normalization, it was possible for the shape recognition at minimum amount of the pixel by giving the weight to the skeleton pixel. As the source images was replaced by the skeleton images., it was possible to reduce the amount of data and computational loads dramatically, and so become much faster even with a smaller memory capacity. Through the experiment, we investigated the optimum scale factor and good result was proved when realizing the pattern recognition system.


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Cite this article
[IEEE Style]
C. C. Seock and S. Y. Koo, "Shape Recognition Using Skeleton Image Based on Mathematical Morphology," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 3, no. 4, pp. 883-898, 1996. DOI: 10.3745/KIPSTE.1996.3.4.883.

[ACM Style]
Chang Chu Seock and Son Yoon Koo. 1996. Shape Recognition Using Skeleton Image Based on Mathematical Morphology. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 3, 4, (1996), 883-898. DOI: 10.3745/KIPSTE.1996.3.4.883.