一种改进的基于模糊聚类的图像分割方法

刘华军; 任明武; 杨静宇

doi:10.11834/jig.200609221

学术论文与技术报告 | 浏览量 : 0 下载量: 251 CSCD: 0

PDF
导出
分享
收藏
专辑

一种改进的基于模糊聚类的图像分割方法
An Improved Image Segmentation Method Based on Fuzzy Clustering
2006年11卷第9期页码：1312
纸质出版：2006
DOI： 10.11834/jig.200609221
稿件说明：

移动端阅览

刘华军, 任明武, 杨静宇. 一种改进的基于模糊聚类的图像分割方法[J]. 中国图象图形学报, 2006,11(9):1312. DOI： 10.11834/jig.200609221.

An Improved Image Segmentation Method Based on Fuzzy Clustering[J]. Journal of Image and Graphics, 2006, 11(9): 1312. DOI： 10.11834/jig.200609221.

摘要

针对亮度不一致的阴影路面的目标分割问题，对使用空间关系约束的模糊聚类算法进行了改进，即首先定义了像素之间以及像素与区域之间的近邻关系，并构造了像素与区域之间的空间关系隶属度矩阵，然后将此矩阵约束到传统的模糊C-均值聚类算法的隶属度矩阵中，最终形成了基于空间关系约束的模糊聚类算法。该算法只需设置很少的参数即可自动完成聚类。该算法在受光照影响导致目标亮度不一致的林荫道道路图像中进行了实验。实验结果表明，该算法对机器人导航中阴影路面的一致性分割方面具有良好的效果。

Abstract

An improved spatial relation constrained FCM algorithm is developed in this paper

the spatial neighbor relation between both pixels and between pixel and regions are defined

and the spatial relation matrix between pixel and regions has been constructed.This matrix is constrained to the partition matrix of the classical fuzzy C-Means clustering(FCM) algorithms and the spatial relation constrained FCM algorithm is formed.This algorithm can automatically segment images with fewer parameters comparing to other algorithms of this category.Many experiments are conducted on the avenue images in which the road intensity is inconsistent

and the results show that our segmentation algorithm has better performance to object's consistency for road images with shadows.