Earticle

초록

영어

Fuzzy c-means algorithm is an unsupervised clustering algorithm, its clustering process can reduce the human intervention, and it is suitable for processing medical images of uncertainty and ambiguity. When simply using FCM algorithm in brain image segmentation will leads to the condition of low accuracy. On the basis of FCM algorithm, this paper proposes a new method which combines FCM algorithm and morphology algorithm. The result of simulation shows that this method can accurately and efficiently segment the brain image. The new algorithm is an effective method for image segmentation.

목차

Abstract
 1. Introduction
 2. The Basic Principle and Method
  2.1. The Basic Principle of Morphology Algorithm
  2.2. The Basic Principle of FCM Algorithm
  2.3. Implementation Steps of the Algorithm
 3. Image Processing by Morphology Algorithm
 4. The Experimental Results and Analysis
  4.1. The Original Image Segmentation
  4.2. The Noisy Image Segmentation
 4. Conclusion
 References

키워드

저자

• Shigang Wang [ School of Mechatronics Engineering, Qiqihar University, Qiqihar, China ]
• Zhinan Rong [ School of Mechatronics Engineering, Qiqihar University, Qiqihar, China ]
• Xueshan Gao [ School of Mechatronics Engineering, Qiqihar University, Qiqihar, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605