吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

基于空间模糊聚类的图像分割优化算法

李岩波1, 韩啸2   

  1. 1. 吉林大学 数学学院, 长春 130012; 2. 吉林大学 学报编辑部, 长春 130012
  • 收稿日期:2014-01-17 出版日期:2014-05-26 发布日期:2014-08-27
  • 通讯作者: 李岩波 E-mail:liyb@jlu.edu.cn

Spatial Fuzzy Clustering Optimization Algorithm for Image Segmentation

LI Yanbo1, HAN Xiao2   

  1. 1. College of Mathematics, Jilin University, Changchun 130012, China;2. Editorial Department of Journal of Jilin University, Changchun 130012, China
  • Received:2014-01-17 Online:2014-05-26 Published:2014-08-27
  • Contact: LI Yanbo E-mail:liyb@jlu.edu.cn

摘要:

针对传统模糊C-均值(FCM)算法抗噪性能差的问题, 提出一种新的基于空间模糊聚类的图像分割优化算法. 该算法通过在传统FCM算法基础上加入图像特征项中像素间的空间位置信息, 解决了传统FCM对噪声敏感的问题, 增强了算法的鲁棒性. 实验结果表明, 对于添加5%Gauss噪声的图像, 该算法可实现有效分割, 分割效果显著优于传统FCM算法.

关键词: 图像分割, 模糊聚类, FCM算法, 空间位置信息

Abstract:

For the poor antinoise performance limitations of the traditional fuzzy C-means (FCM) algorithm, we proposed a new spatial fuzzy clustering optimization algorithm for image segmentation. We added a wealth of spatial information between pixels in the image feature items, so that the traditional FCM sensitive
to noise was solved, and the robustness of the algorithm was enhanced. Experimental results show that our algorithm can achieve the effectivesegmentation of the 5% Gaussian noise images, and the results are significantly better than those by traditional FCM image segmentation algorithm.

Key words: image segmentation, fuzzy clustering, FCM algorithm, spatial information

中图分类号: 

  • TP391