| 引用本文: | 王丹,吴孟达.粗糙模糊C-均值算法及其在图像聚类中的应用.[J].国防科技大学学报,2007,29(2):76-80.[点击复制] |
| WANG Dan,WU Mengda.Rough Fuzzy C-Means Algorithm and Its Application to Image Clustering[J].Journal of National University of Defense Technology,2007,29(2):76-80[点击复制] |
|
| |
|
|
| 本文已被：浏览 6720次 下载 5873次 |
| 粗糙模糊C-均值算法及其在图像聚类中的应用 |
| 王丹, 吴孟达 |
|
(国防科技大学 理学院，湖南 长沙 410073)
|
| 摘要: |
| 提出一种新的粗糙模糊C均值算法（RFCM），该算法基于粗糙集的上、下近似的概念改进了FCM的目标函数，从而改变了隶属度函数的分布，使得隶属度函数的分布更加合理，同时RFCM的时间复杂性比FCM更低。将RFCM用于图像的聚类，相对于FCM算法，图像的边缘更光滑，同时对初始隶属度矩阵敏感度更低。该算法具有较好的稳定性，是一种实用的算法。 |
| 关键词: 粗糙集 模糊C-均值算法 粗糙模糊C-均值算法 |
| DOI： |
| 投稿日期：2006-11-09 |
| 基金项目:国防科技大学资助项目(JC03-02-003) |
|
| Rough Fuzzy C-Means Algorithm and Its Application to Image Clustering |
| WANG Dan, WU Mengda |
|
(College of Science, National Univ. of Defense Technology, Changsha 410073，China)
|
| Abstract: |
| Based on the rough set model proposed by Pawlak, a new fuzzy C-means algorithm-rough fuzzy C-means algorithm (RFCM) is presented. The algorithm employs a new objective function which incorporates the concepts of the upper approximation and the lower approximation in rough sets, and which produces better results than Fuzzy C-mean algorithm at time complexity, clustering precision, the sensitivity to initial degree of membership matrix. The better effect can be testified by many experiments. |
| Keywords: rough sets fuzzy C-mean algorithm rough fuzzy C-means algorithm |
|
|
