A novel robust and fast Segmentation of the Color Images using Fuzzy Classification C-means
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Date
2010
Authors
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Journal ISSN
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Publisher
IEEE
Abstract
This paper brings out a method for segmentation of color images based on fuzzy classification. It proceeds in a first step by a fine segmentation using the algorithm of fuzzy cmeans (FCM). The method then applies a test fusion of fuzzy classes. The result is a coarse segmentation, where each region is the union of elementary regions grown from FCM. The fuzzy C-Means (FCM) clustering is an iterative partitioning method that produces optimal c-partitions, the standard FCM algorithm takes a long time to partition a large data set. The proposed FCM program must read the entire data set into a memory for processing. Our results show that the system performance is robust to different types of images.
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Keywords
Segmentation, Classification, FUZlJ'Logic, FCM, Merge regions, Optimal c-partitions.
Citation
Toure, M. L., Beiji, Z., & Musau, F. (2010). A novel robust and fast Segmentation of the Color Images using Fuzzy Classification C-means. In 2nd International Conforence on Education Technology and Computer (ICETC), pp. V4-341-V4-344. https://doi: 10.1109/ICETC.2010.5529667.