Image Segmentation by Fuzzy C-Means Clustering Algorithm

Wang Hechun; Gong Xunkai

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Image Segmentation by Fuzzy C-Means Clustering Algorithm

更新时间：2020-08-12

- Image Segmentation by Fuzzy C-Means Clustering Algorithm
- Optics and Precision Engineering Vol. 0, Issue 4, Pages: 65-70(1991)
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- Published Online：15 August 1991，
  
  Published：15 August 1991
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王和春, 宫迅凯. 用模糊聚类Fuzzy C-Means算法实现图像分割[J]. 光学精密工程, 1991,(4): 65-70

Wang Hechun, Gong Xunkai. Image Segmentation by Fuzzy C-Means Clustering Algorithm[J]. Editorial Office of Optics and Precision Engineering, 1991,(4): 65-70
王和春, 宫迅凯. 用模糊聚类Fuzzy C-Means算法实现图像分割[J]. 光学精密工程, 1991,(4): 65-70 DOI：

Wang Hechun, Gong Xunkai. Image Segmentation by Fuzzy C-Means Clustering Algorithm[J]. Editorial Office of Optics and Precision Engineering, 1991,(4): 65-70 DOI：

摘要

本文描述了一种有效的Fuzzy C-Means(FCM)聚类算法的数学原理及其在图像分割中的应用

该算法的主要特点是提供了一种非监督的模糊聚类方式。为了减少计算量

文章引入了塔型数据结构PDS(Pyramid Data Structure)

并对FCM算法的初始模糊矩阵的选取和实验结果进行了讨论。

Abstract

The mathematical principle of the effective fuzzy c-means (FCM) algorithm and its application for image segmentation are described. This algorithm is characterized by unsupervised clustering. The pyramid data structure (PDS) can be used to reduce amount of computation

and both the choice of the initial matrix of the FCM algorithm and experimental results arediscussed.

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