基于模糊聚类的图像分割研究进展

doi:10.3969/j.issn.0372-2112.2019.08.023

电子学报 ›› 2019, Vol. 47 ›› Issue (8): 1776-1791.DOI: 10.3969/j.issn.0372-2112.2019.08.023

基于模糊聚类的图像分割研究进展

雷涛^1,4, 张肖², 加小红², 刘侍刚³, 张艳宁⁴

1. 陕西科技大学电子信息与人工智能学院, 陕西西安 710021;
2. 陕西科技大学电气与控制工程学院, 陕西西安 710021;
3. 陕西师范大学计算机科学学院, 陕西西安 710062;
4. 西北工业大学计算机科学学院, 陕西西安 710072

收稿日期:2018-08-07 修回日期:2019-02-25 出版日期:2019-08-25
- 作者简介:
- 雷涛男,1981年11月出生,陕西大荔人.2011年在西北工业大学获得博士学位,现为陕西科技大学教授,博士生导师.主要从事图像处理、模式识别和计算机视觉等方面的研究工作.E-mail:leitao@sust.edu.cn;张肖女,1993年10月出生,陕西兴平人.硕士研究生.主要从事图像处理和模式识别方面的研究工作.E-mail:zhangxanny@163.com
- 基金资助:
- 国家自然科学基金 (No.61871259，No.61811530325，No.61461025，No.61672333，No.61873155）

Research Progress on Image Segmentation Based on Fuzzy Clustering

LEI Tao^1,4, ZHANG Xiao², JIA Xiao-hong², LIU Shi-gang³, ZHANG Yan-ning⁴

1. School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi'an, Shaanxi 710021, China;
2. School of Electronical and Control Engineering, Shaanxi University of Science and Technology, Xi'an, Shaanxi 710021, China;
3. School of Computer Science, Shaanxi Normal University, Xi'an, Shaanxi 710062, China;
4. School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, China

Received:2018-08-07 Revised:2019-02-25 Online:2019-08-25 Published:2019-08-25
- Supported by:
- National Natural Science Foundation of China (No.61871259, No.61811530325, No.61461025, No.61672333, No.61873155)

摘要/Abstract

摘要： 模糊聚类算法（Fuzzy C-Means，FCM）是一种基于软划分的聚类过程，已被广泛应用于机器学习、图像处理和计算机视觉等领域.虽然当前已涌现出大量关于FCM的图像分割算法，但仍然面临诸多挑战.本文将基于FCM的图像分割算法归纳为三类：基于空间邻域信息的FCM算法、基于直方图信息的快速FCM算法及基于维度加权的FCM算法.首先系统分析和阐述了各类FCM算法的研究现状，然后通过实验分析各类算法的性能，最后总结了FCM算法在图像分割中存在的问题以及将来的研究方向.

关键词: 图像分割, 模糊聚类算法, 邻域信息, 直方图, 隐马尔科夫模型

Abstract: Fuzzy c-means (FCM) algorithm is a clustering process based on soft partitioning,and it has been widely used in machine learning, image processing and computer vision. Although a large number of image segmentation algorithms based on FCM have been proposed, it is still a challenge research topic to research image segmentation based on fuzzy clustering. In this paper, image segmentation algorithms based on FCM are roughly grouped into three categories: FCM algorithms based on spatial neighboring information, FCM algorithms based on histogram information,and FCM algorithms based on dimension weight. We firstly analyze and elaborate the current research on FCM algorithms. Afterwards, we analyze the performance of different algorithms according to experiments.Finally,we conclude the drawbacks of image segmentation algorithms based on FCM and the future research direction.

Key words: image segmentation, fuzzy c-means clustering, neighboring information, histogram, Hidden Markov model

中图分类号:

TP391.41

雷涛, 张肖, 加小红, 等. 基于模糊聚类的图像分割研究进展[J]. 电子学报, 2019, 47(8): 1776-1791.

LEI Tao, ZHANG Xiao, JIA Xiao-hong, et al. Research Progress on Image Segmentation Based on Fuzzy Clustering[J]. Acta Electronica Sinica, 2019, 47(8): 1776-1791.

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基于模糊聚类的图像分割研究进展

Research Progress on Image Segmentation Based on Fuzzy Clustering

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