使用高效的c均值聚類算法的圖象閾值化方法
THRESHOLDING OF IMAGES USING AN EFFICIENT c-MEAN CLUSTERING ALGORITHM
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摘要: Otsu(1979)的閾值化法被認(rèn)為是一種良好的圖象分割方法。本文提出一個(gè)適合圖象分割的高效的c均值聚類算法。它與Otsu法有完全相同的分割結(jié)果,但計(jì)算時(shí)間約減少了一個(gè)數(shù)量級(jí)。
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關(guān)鍵詞:
- 圖象分割; 閾值比; c均值聚類算法
Abstract: Otsu s method (1979) is considered as a good thresholding method for image segmentation. In this paper, an efficient c-mean calustring algorithm which is suitable for image segmentation is proposed. It yields th came results as Otsu s method, but its computational time is about one order of magnitude less than that of Otsu s method. -
P. K.Sahoo et al., Computer Vision, Graphics, and Image Processing, 41(1988)2, 233-260.[2]S. U. Lee et al., Computer Vision, Graphics, and Image Processing, 52(1990)2, 171-190.[3]N. Otsu, IEEE Trans. on SMC, SMC-9(1979)1, 62-66.[4]J. C.Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, New York: Plenum, (1981). -
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