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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 12    
Website: http://www.ijser.org
scirp IJSER >> Volume 2, Issue 12, December 2011
An Efficient Algorithm for Segmentation Using Fuzzy Local Information C-Means Clustering
Full Text(PDF, 3000)  PP.  
Author(s)
Sandeep Kumar Mekapothula, V. Jai Kumar
KEYWORDS
Clustering, Fuzzy C-means, Fuzzy constraints, gray level constraints, image segmentation, and spatial constraints
ABSTRACT
In this paper there is a variation of fuzzy c-means (FCM) algorithm is presented that provides image clustering. The proposed algorithm incorporates local spatial information and gray level information in a novel fuzzy way. The new algorithm is called fuzzy local information C-Means (FLICM). By using this algorithm we can overcome the disadvantages of the previous algorithms and at the same time enhances the clustering performance. The major characteristic of this FLICM is the use of a fuzzy local (both spatial and gray level) similarity measure, aiming to guarantee noise insensitiveness and image detail preservation. Furthermore, the proposed algorithm is fully free of the empirically adjusted parameters (a, ?g, ?s, etc.). Experiments performed on some synthetic and real images shows that this algorithm is effective and efficient, providing high robustness to noisy images.
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