한국지능정보시스템학회:학술대회논문집 (Proceedings of the Korea Inteligent Information System Society Conference)
- 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
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- Pages.313-320
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- 1999
Fuzzy Mean Method with Bispectral Features for Robust 2D Shape Classification
- Woo, Young-Woon (Dept. of Computer Eng., Dongeui Univ) ;
- Han, Soo-Whan (Dept. of Multimedia Eng., Dongeui Univ.)
- 발행 : 1999.10.01
초록
In this paper, a translation, rotation and scale invariant system for the classification of closed 2D images using the bispectrum of a contour sequence and the weighted fuzzy mean method is derived and compared with the classification process using one of the competitive neural algorithm, called a LVQ(Learning Vector Quantization). The bispectrun based on third order cumulants is applied to the contour sequences of the images to extract fifteen feature vectors for each planar image. These bispectral feature vectors, which are invariant to shape translation, rotation and scale transformation, can be used to represent two-dimensional planar images and are fed into an classifier using weighted fuzzy mean method. The experimental processes with eight different shapes of aircraft images are presented to illustrate the high performance of the proposed classifier.