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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Multi-level Thresholding Using Entropy-Based Weighted FCM Algorithm in Color Image
verfasst von : Jun-Taek Oh, Hyun-Wook Kwak, Young-Ho Sohn, Wook-Hyun Kim
Erschienen in: Advances in Visual Computing
Verlag: Springer Berlin Heidelberg
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This paper proposes a multi-level thresholding method based on a weighted FCM(Fuzzy C-Means) algorithm in color image. FCM algorithm can determine a more optimal thresholding value than existing methods and be extended to multi-level thresholding, yet it is sensitive to noise, as it does not include spatial information. To solve this problem, a weight based on the entropy obtained from neighboring pixels is applied to FCM algorithm, and the optimal cluster number is determined using the within-class distance in the code image based on the clustered pixels for each color component. Experiments confirmed that the proposed method was more tolerant to noise and superior to existing methods.