Image Segmentation Using an Extended Fuzzy Clustering Algorithm

확장된 퍼지 클러스터링 알고리즘을 이용한 영상 분할

  • 김수환 (고려대학교 전자공학과) ;
  • 강경진 (고려대학교 전자공학과) ;
  • 이태원 (고려대학교 전자공학과)
  • Published : 1992.03.01

Abstract

Recently, the fuzzy theory has been adopted broadly to the applications of image processing. Especially the fuzzy clustering algorithm is adopted to image segmentation to reduce the ambiguity and the influence of noise in an image.But this needs lots of memory and execution time because of the great deal of image data. Therefore a new image segmentation algorithm is needed which reduces the memory and execution time, doesn't change the characteristices of the image, and simultaneously has the same result of image segmentation as the conventional fuzzy clustering algorithm. In this paper, for image segmentation, an extended fuzzy clustering algorithm is proposed which uses the occurence of data of the same characteristic value as the weight of the characteristic value instead of using the characteristic value directly in an image and it is proved the memory reduction and execution time reducted in comparision with the conventional fuzzy clustering algorithm in image segmentation.

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