Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Space Partition using Context Fuzzy c-Means Algorithm for Image Segmentation

영상 분할을 위한 Context Fuzzy c-Means 알고리즘을 이용한 공간 분할

  • 노석범 (대전대학교 컴퓨터공학과) ;
  • 안태천 (원광대학교 전자 및 제어공학부) ;
  • 백용선 (대덕대학 컴퓨터웹정보과) ;
  • 김용수 (대전대학교 컴퓨터공학과)
  • Received : 2010.04.03
  • Accepted : 2010.05.24
  • Published : 2010.06.25
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Abstract

Image segmentation is the basic step in the field of the image processing for pattern recognition, environment recognition, and context analysis. The Otsu's automatic threshold selection, which determines the optimal threshold value to maximize the between class scatter using the distribution information of the normalized histogram of a image, is the famous method among the various image segmentation methods. For the automatic threshold selection proposed by Otsu, it is difficult to determine the optimal threshold value by considering the sub-region characteristic of the image because the Otsu's algorithm analyzes the global histogram of a image. In this paper, to alleviate this difficulty of Otsu's image segmentation algorithm and to improve image segmentation capability, the original image is divided into several sub-images by using context fuzzy c-means algorithm. The proposed fuzzy Otsu threshold algorithm is applied to the divided sub-images and the several threshold values are obtained.

영상 분할 (Image Segmentation)은 패턴 인식, 환경 인식, 문서 분석을 위한 영상 처리 과정에서 가장 기본적인 단계이다. 영상 분할 방법들 중 Otsu의 영상의 정규화된 히스토그램의 분포 정보를 이용하여 클래스 간의 분산을 최대화 시키는 임계치값을 결정하는 자동 임계치값 선정방법이 가장 잘 알려진 방법이다. Otsu의 방법은 영상의 전 영역에 대한 히스토그램을 분석함으로써 영상의 부분적인 특성을 반영하여 임계치값을 결정하기는 어렵다. 본 논문에서는 이 어려움 해소하기 위하여 Context Fuzzy c-Means 알고리즘을 이용하여 영상을 여러 개의 부분 영역으로 나누고, 정의된 부 영역에 영상 분할 기법을 적용함으로써 부 영역들에 적합한 여러 개의 임계치값을 계산함으로써 영상 분할 성능을 개선하고자 하였다.

Keywords

References

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