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An empirical analysis of colour image segmentation using fuzzy c-means clustering

journal contribution
posted on 2010-01-01, 00:00 authored by Chee Peng LimChee Peng Lim, W Ooi
In this paper, an empirical analysis to examine the effects of image segmentation with different colour models using the fuzzy c-means (FCM) clustering algorithm is conducted. A qualitative evaluation method based on human perceptual judgement is used. Two sets of complex images, i.e., outdoor scenes and satellite imagery, are used for demonstration. These images are employed to examine the characteristics of image segmentation using FCM with eight different colour models. The results obtained from the experimental study are compared and analysed. It is found that the CIELAB colour model yields the best outcomes in colour image segmentation with FCM.

History

Journal

International journal of knowledge engineering and soft data paradigms

Volume

2

Issue

1

Pagination

97 - 106

Publisher

Inderscience Publishers

Location

Geneva, Switzerland

ISSN

1755-3210

eISSN

1755-3229

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Copyright notice

2010, Inderscience Enterprises Ltd.

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