Title :
S-function based novel fuzzy clustering algorithm for image segmentation
Author :
Maokai Yuan ; Liping Chen ; Jianqiang Wang ; Shuguang Zhao
Author_Institution :
Coll. of Inf. Sci. & Technol., Donghua Univ., Shanghai, China
Abstract :
The clustering methods based on Fuzzy C-Means (FCM) are frequently used in image-segmentation. But the standard FCM algorithm has some defects, especially ignoring the pixel spatial information´s influence on the classification result. For the sake of a more reasonable objective function, an improved FCM algorithm is proposed in this paper, which uses spatial information and S-function to determine the weight coefficients of the objective function. Experimental results show that the proposed algorithm has better performance than the standard FCM algorithm.
Keywords :
fuzzy set theory; image segmentation; pattern clustering; S-function; clustering methods; image segmentation; objective function; spatial information; standard fuzzy c-means algorithm; weight coefficients; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Correlation; Image edge detection; Image segmentation; Indexes; S-function; fuzzy C-means; image segmentation; spatial information;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-180-9
DOI :
10.1109/FSKD.2011.6019882