Journal of Graphics
Previous Articles Next Articles
Online:
Published:
Abstract: This paper proposes a new algorithm based on traditional fuzzy C-means algorithm regard to the noise and uneven light in medical images. Fuzzy C-means clustering algorithm has been rapid developed in image segmentation applications, as simple description, easy to implement, works well for segmentation. But there are also other issues such as noise sensitive. Considering that the medical images data must contain noise, a modified objective function J(u, v) has been proposed, adding a punishment factor on the basis of introducing the pixel neighborhood information. The new algorithm covers the shortage of traditional fuzzy C-means clustering algorithm, which makes the algorithm clustering with noise more effectively. Experimental results show that the algorithm is effective and practical.
Key words: fuzzy clustering, neighborhood pixels, punishment factor, medical image segmentation
Su Zhiyuan, Liu Hui, Li Qiuping. Research of Anti-Noise Image Segmentation Method Based on Fuzzy C-Means[J]. Journal of Graphics.
0 / / Recommend
Add to citation manager EndNote|Ris|BibTeX
URL: http://www.txxb.com.cn/EN/
http://www.txxb.com.cn/EN/Y2015/V36/I3/477