使用高效的c均值聚类算法的图象阈值化方法
THRESHOLDING OF IMAGES USING AN EFFICIENT c-MEAN CLUSTERING ALGORITHM
-
摘要: Otsu(1979)的阈值化法被认为是一种良好的图象分割方法。本文提出一个适合图象分割的高效的c均值聚类算法。它与Otsu法有完全相同的分割结果,但计算时间约减少了一个数量级。
-
关键词:
- 图象分割; 阈值比; c均值聚类算法
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). -
计量
- 文章访问数: 2129
- HTML全文浏览量: 125
- PDF下载量: 594
- 被引次数: 0
下载:
