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Multi-level thresholding using Entropy-based Weighted FCM Algorithm in Color Image  

Oh, Jun-Taek (Department of Computer Engineering, Yeungnam University)
Kwak, Hyun-Wook (Department of Computer Engineering, Yeungnam University)
Kim, Wook-Hyun (School of Electrical Engineering and Computer Science, Yeungnam University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.42, no.6, 2005 , pp. 73-82 More about this Journal
Abstract
This paper proposes a multi-level thresholding method using weighted FCM(Fuzzy C-Means) algorithm in color image. FCM algerian determines a more optimal thresholding value than the existing methods and can extend to multi-level thresholding. But FCM algerian is sensitive to noise because it doesn't include spatial information. To solve the problem, we can remove noise by applying a weight based on entropy that is obtained from neighboring pixels to FCM algerian. And we determine the optimal cluster number by using within-class distance in code image based on the clustered pixels of each color component. In the experiments, we show that the proposed method is more tolerant to noise and is more superior than the existing methods.
Keywords
Color image multi-level thresholding; Weighted FCM(Fuzzy C-Means); Entropy; Within-class distance;
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