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An empirical analysis of colour image segmentation using fuzzy c-means clustering
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.
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Journal
International journal of knowledge engineering and soft data paradigmsVolume
2Issue
1Pagination
97 - 106Publisher
Inderscience PublishersLocation
Geneva, SwitzerlandISSN
1755-3210eISSN
1755-3229Language
engPublication classification
C1.1 Refereed article in a scholarly journalCopyright notice
2010, Inderscience Enterprises Ltd.Usage metrics
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