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Advances in Fuzzy Systems
Volume 2016 (2016), Article ID 6238295, 10 pages
Research Article

Robust FCM Algorithm with Local and Gray Information for Image Segmentation

Laboratory of Innovative Technologies, National School of Applied Sciences, Tangier, Morocco

Received 25 July 2016; Revised 8 September 2016; Accepted 21 September 2016

Academic Editor: Gözde Ulutagay

Copyright © 2016 Hanane Barrah et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The FCM (fuzzy -mean) algorithm has been extended and modified in many ways in order to solve the image segmentation problem. However, almost all the extensions require the adjustment of at least one parameter that depends on the image itself. To overcome this problem and provide a robust fuzzy clustering algorithm that is fully free of the empirical parameters and noise type-independent, we propose a new factor that includes the local spatial and the gray level information. Actually, this work provides three extensions of the FCM algorithm that proved their efficiency on synthetic and real images.