Fuzzy Classifier and Bispectrum for Invariant 2-D Shape Recognition

2차원 불변 영상 인식을 위한 퍼지 분류기와 바이스펙트럼

  • 한수환 (동의대학교 멀티미디어공학과) ;
  • 우영운 (동의대학교 컴퓨터공학과)
  • Published : 2000.06.01


In this paper, a translation, rotation and scale invariant system for the recognition of closed 2-D images using the bispectrum of a contour sequence and a weighted fuzzy classifier is derived and compared with the recognition process using one of the competitive neural algorithm, called a LVQ( Loaming Vector Quantization). The bispectrum based on third order cumulants is applied to the contour sequences of an image 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 the represent two-dimensional planar images and are fed into a weighted fuzzy classifier. The experimental processes with eight different shapes of aircraft images are presented to illustrate a relatively high performance of the proposed recognition system.