Fuzzy clustering of color and texture features for image segmentation: a study on satellite image retrieval

Ooi, W. S. and Lim, C. P. 2006, Fuzzy clustering of color and texture features for image segmentation: a study on satellite image retrieval, Journal of intelligent and fuzzy systems, vol. 17, no. 3, pp. 297-311.

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Title Fuzzy clustering of color and texture features for image segmentation: a study on satellite image retrieval
Author(s) Ooi, W. S.
Lim, C. P.
Journal name Journal of intelligent and fuzzy systems
Volume number 17
Issue number 3
Start page 297
End page 311
Total pages 15
Publisher IOS Press
Place of publication Amsterdam, The Netherlands
Publication date 2006
ISSN 1064-1246
1875-8967
Keyword(s) Co-occurrence matrix
Color space quantization
Fuzzy c-means clustering
Image region extraction
Image segmentation
Satellite image retrieval
Summary In this paper, a new image segmentation approach that integrates color and texture features using the fuzzy c-means clustering algorithm is described. To demonstrate the applicability of the proposed approach to satellite image retrieval, an interactive region-based image query system is designed and developed. A database comprising 400 multispectral satellite images is used to evaluate the performance of the system. The results are analyzed and discussed, and a performance comparison with other methods is included. The outcomes reveal that the proposed approach is able to improve the quality of the segmentation results as well as the retrieval performance.
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30048723

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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