Performance characterization of clustering algorithms for colour image segmentation

被引：0
|
作者：
Ilea, D. E. [1 ]
Whelan, P. F. [1 ]
Ghita, O. [1 ]
机构：
[1] Dublin City Univ, Sch Elect Engn, Vis Syst Grp, Dublin 9, Ireland
来源：
PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON OPTIMIZATION OF ELECTRICAL AND ELECTRONIC EQUIPMENT, VOL IV | 2006年
关键词：
colour image segmentation; Fuzzy clustering; competitive agglomeration; diffusion based filtering; image segmentation;
D O I：
暂无
中图分类号：
G40 [教育学];
学科分类号：
040101 ; 120403 ;
摘要：
This paper details the implementation of three traditional clustering techniques (K-Means clustering, Fuzzy C-Means clustering and Adaptive K-Means clustering) that are applied to extract the colour information that is used in the image segmentation process. The aim of this paper is to evaluate the performance of the analysed colour clustering techniques for the extraction of optimal features from colour spaces and investigate which method returns the most consistent results when applied on a large suite of mosaic images.
引用
收藏
页码：137 / 142
页数：6
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