基于模糊C-均值聚类图像分割技术研究  

Based on the Fuzzy C-means Clustering Image Segmentation Technology Research

作　　者：任燕[1] 

机构地区：[1]青岛酒店管理职业技术学院,山东青岛266100

出　　处：《科技通报》2012年第4期206-208,共3页Bulletin of Science and Technology

摘　　要：主要研究了均值聚类图像分割问题。针对传统的聚类图像分割算法对图像地分割精度较低等问题,提出一种基于模糊控制的C-均值聚类快速图像分割新方法。本文采用快速模糊C-均值聚类算法对图像分割。实验结果表明,图像分割边缘清晰,分割效果明显优于传统的聚类图像分割算法。This paper mainly studies the means clustering image segmentation. In view of the traditional clustering image segmentation algorithm for image segmentation accuracy is low problem, put forward a kind of fuzzy control based on C - means clustering image segmentation method. Methods firstly in clustering image segmentation algorithm based on fast, using fuzzy C - means clustering algorithm for image segmentation. The experimental results show that the algorithm in clustering, to optimize the performance of the same premise, image segmentation edge clear, segmentation better than tra- ditional clustering algorithm for image segmentation.

关 键 词：图像分割 模糊 均值聚类算法 优化 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]