Clustering of Image Data Using K-Means and Fuzzy K-Means

被引：1
|
作者：
Rahmani, Md. Khalid Imam [1 ]
Pal, Naina [1 ]
Arora, Kamiya [1 ]
机构：
[1] Echelon Inst Technol, Dept Comp Sci & Engn, Faridabad, India
来源：
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS | 2014年 / 5卷 / 07期
关键词：
Clustering; Segmentation; K-Means Clustering; Fuzzy K-Means;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Clustering is a major technique used for grouping of numerical and image data in data mining and image processing applications. Clustering makes the job of image retrieval easy by finding the images as similar as given in the query image. The images are grouped together in some given number of clusters. Image data are grouped on the basis of some features such as color, texture, shape etc. contained in the images in the form of pixels. For the purpose of efficiency and better results image data are segmented before applying clustering. The technique used here is K-Means and Fuzzy K-Means which are very time saving and efficient.
引用
收藏
页码：160 / 163
页数：4
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