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International Conference on Mechanical Engineering and Technology (ICMET-London 2011)

Garry Lee
Garry Lee
Information Engineering Research Institute
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ASME Press
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This paper discusses the application of Culture Algorithm to Fuzzy C-means clustering. The aim is to improve the quality of image segmentation. Fuzzy C-means clustering algorithm as one of the fuzzy clustering is widely used in image segmentation. We use Culture Algorithm to initialize centre of clusters to make Fuzzy C-means robust against initialization. The proposed method can effectively avoid being trapped into local optimum as well. The analysis has shown that Fuzzy Clustering based on Culture Algorithm can obtain better total clustering accuracy with high efficiency, and the quality of image segmentation is improved.

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