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An improved Spatial FCM algorithm Based on Artificial Bees Colony

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Author(s): Ouadfel Salima | Abdelmalik Taleb-Ahmed | Batouche Mohamed

Journal: IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN 2252-8938

Volume: 1;
Issue: 3;
Start page: 149;
Date: 2012;
Original page

Keywords: Image segmentation | Fuzzy C-means | Optimization | Spatial information | ABC algorithm.

ABSTRACT
In this paper, we presented a new spatial fuzzy clustering algorithm optimised by the Artificial Bees Colony (ABC) algorithm. By introducing the global search of ABC algorithm into the spatial Fuzzy C-Means Clustering algorithm, a new kind of methods (SFCM-ABC) is proposed. SFCM-ABC has two major characteristics. First it tackles better noisy image segmentation by making use of the spatial local information into the membership function. Secondly, it improves the global performance by taking advantages of the globalized search in the entire solution space of ABC rather than a localized searching like in FCM algorithm. Experiments with synthetic and real images show that SFCM-ABC is robust to noise compared to other methods
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