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

Issue title: MASOCR Workshop

Article type: Research Article

Authors: Ooi, W.S. | Lim, C.P.

Affiliations: School of Electrical and Electronic Engineering, University of Science Malaysia, Engineering Campus, 14300, Nibong Tebal, Penang, Malaysia

Note: [] Corresponding author. Tel.: +604 5996033; Fax: +604 5941023; E-mail: cplim@eng.usm.my

Abstract: 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.

Keywords: Image segmentation, fuzzy c-means clustering, color space quantization, co-occurrence matrix, image region extraction, satellite image retrieval

Journal: Journal of Intelligent & Fuzzy Systems, vol. 17, no. 3, pp. 297-311, 2006