计算机科学 ›› 2018, Vol. 45 ›› Issue (11A): 247-250.

• 模式识别与图像处理 • 上一篇    下一篇

结合爬山法的模糊C均值彩色图像分割方法

贾娟娟1, 贾富杰2   

  1. 兰州理工大学技术工程学院 兰州7300501
    兰州大学数学与统计学院 兰州7300002
  • 出版日期:2019-02-26 发布日期:2019-02-26
  • 通讯作者: 贾娟娟(1987-),女,硕士,讲师,主要研究方向为数字图像处理,E-mail:jiajuanjuan87@126.com
  • 作者简介:贾富杰(1991-),男,硕士生,主要研究方向为偏微分方程与动力系统。

Fuzzy C-means Color Image Segmentation Algorithm Combining Hill-climbing Algorithm

JIA Juan-juan1, JIA Fu-jie2   

  1. College of Technology and Engineering,Lanzhou University of Technology,Lanzhou 730050,China1
    School of Mathematics and Statistics,Lanzhou University,Lanzhou 730000,China2
  • Online:2019-02-26 Published:2019-02-26

摘要: 采用传统的模糊C均值聚类(FCM)算法进行彩色图像分割存在聚类数的选取、初始聚类中心的确定、迭代过程中的大计算量及后处理等问题。在对上述问题进行研究的基础上,针对传统FCM聚类分割时初始值选取方法的盲目性和随机性,为了更准确地自动获取待分割图像聚类的初始参数,提出了一种结合爬山法的模糊C均值彩色图像分割方法(HFCM),该方法可根据待分割图像的三维颜色直方图自适应地获取FCM算法的初始聚类中心及聚类数目,同时提出一种最频滤波与区域合并相结合的新的后处理策略,有效消除了小的空间区域。实验表明,相对于传统FCM,该图像分割方法的速度较快,并且分割结果更接近人类分割效果。

关键词: 彩色图像分割, 模糊C均值聚类算法, 爬山法, 三维颜色直方图

Abstract: There are some problems with the color image segmentation technology based on traditional Fuzzy C-means clustering algorithm,such as the selection of the initial category number,the determinated of the initial centroids,large amount of calculation in clustering process and post-processing.Based on the research of these problems,according to the shortage of random initialization in traditional FCM,and for getting more accurate initialization automatically,this paper proposed a clustering segmentation method combining Hill-climbing for color image(HFCM),which can generate the initial centroids and the number of clusters adaptively according to the three dimensional histogram of the image.In addition,a new post-processing strategy which combined the most frequency filter and region mergeing was introduced to effectively eliminate small spatial regions.Experiments show that the proposed segmentation algorithm achieves high computational speed,and its segmentation results are close to human perceptions.

Key words: Color image segmentation, Fuzzy C-means clustering algorithm, Global three-dimensional color histogram, Hill-climbing algorithm

中图分类号: 

  • TP391.41
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