A Multi-threshold Image Segmentation Algorithm Based on Weighting Fuzzy c-Means Clustering and Statistical Test

GAO Xin-bo; LI Jie; JI Hong-bing

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A Multi-threshold Image Segmentation Algorithm Based on Weighting Fuzzy c-Means Clustering and Statistical Test

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- A Multi-threshold Image Segmentation Algorithm Based on Weighting Fuzzy c-Means Clustering and Statistical Test
- Acta Electronica Sinica Vol. 32, Issue 4, Pages: 661-664(2004)
- 作者机构：
  
  西安电子科技大学电子工程学院,陕西,西安,710071
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.41
- Published：2004
- 稿件说明：
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GAO Xin-bo, LI Jie, JI Hong-bing. A Multi-threshold Image Segmentation Algorithm Based on Weighting Fuzzy c-Means Clustering and Statistical Test[J]. Acta Electronica Sinica, 2004, 32(4): 661-664.
DOI：

GAO Xin-bo, LI Jie, JI Hong-bing. A Multi-threshold Image Segmentation Algorithm Based on Weighting Fuzzy c-Means Clustering and Statistical Test[J]. Acta Electronica Sinica, 2004, 32(4): 661-664. DOI：

摘要

图像分割是计算机视觉中一个重要的研究课题.本文提出一种基于直方图的多阈值灰度图像自动分割方法

该方法利用加权模糊

-均值聚类算法快速实现分割过程

同时通过单峰统计检验指导来自动确定多阈值的合适数目.实验结果表明了该方法的有效性.

Abstract

Image segmentation is an important research topic in the field of computer vision.A histogram-based multi-threshold automatic segmentation method is presented for gray scale images.On the one hand

it uses the weighting fuzzy

-mean clustering algorithm to fast implement the segmentation procedure;on the other hand

it automatically determines the proper number of threshold via unimode statistical test.The experimental result illustrates the effectiveness of the proposed method.

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