Journal of the Institute of Electronics Engineers of Korea SP (대한전자공학회논문지SP)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Multi-level thresholding using Entropy-based Weighted FCM Algorithm in Color Image

Entropy 기반의 Weighted FCM 알고리즘을 이용한 컬러 영상 Multi-level thresholding

  • Oh, Jun-Taek (Department of Computer Engineering, Yeungnam University) ;
  • Kwak, Hyun-Wook (Department of Computer Engineering, Yeungnam University) ;
  • Kim, Wook-Hyun (School of Electrical Engineering and Computer Science, Yeungnam University)
  • 오준택 (영남대학교 컴퓨터공학과) ;
  • 곽현욱 (영남대학교 컴퓨터공학과) ;
  • 김욱현 (영남대학교 전자정보공학부)
  • Published : 2005.11.01
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Abstract

This paper proposes a multi-level thresholding method using weighted FCM(Fuzzy C-Means) algorithm in color image. FCM algerian determines a more optimal thresholding value than the existing methods and can extend to multi-level thresholding. But FCM algerian is sensitive to noise because it doesn't include spatial information. To solve the problem, we can remove noise by applying a weight based on entropy that is obtained from neighboring pixels to FCM algerian. And we determine the optimal cluster number by using within-class distance in code image based on the clustered pixels of each color component. In the experiments, we show that the proposed method is more tolerant to noise and is more superior than the existing methods.

본 논문은 weighted FCM(Fuzzy C-Means) 알고리즘을 적용한 컬러 영상 multi-level thresholding을 제안한다. FCM 알고리즘은 기존의 thresholding 방법들과 달리 최적의 임계치를 결정할 수 있으며 multi-level thresholding으로의 확장이 가능하다. 그러나 공간정보를 포함하고 있지 않기 때문에 잡음 등에 민감하다는 단점을 가진다. 본 논문은 이러한 단점을 해결하기 위해서 이웃 화소들로부터 얻은 entropy 기반의 가중치(weight)를 FCM 알고리즘에 적용함으로써 잡음의 제거가 가능하다. 그리고 각 색상별 성분의 군집 화소들을 기반으로 생성한 코드 영상에 대해서 군집 내부의 거리값을 이용하여 최적의 군집수를 결정한다. 실험에서 제안한 방법이 기존의 방법들보다 잡음에 대해서 강건하며 우수한 분할 성능을 보였다.

Keywords

References

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