A new descriptor for textured image segmentation based on fuzzy type-2 clustering approach
by Lotfi Tlig; Mounir Sayadi; Farhat Fnaiech
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 7, No. 3, 2014

Abstract: In this paper we present a novel segmentation approach that performs fuzzy clustering and feature extraction. The proposed method consists to forming a new descriptor combining a set of texture sub-features derived from the Grating Cell Operator (GCO) responses of an optimised Gabor filter bank, and Local Binary Pattern (LBP) outputs. The new feature vector offers two advantages. First, it only considers the optimised filters. Second, it aims to characterise both micro and macro textures. In addition, an extended version of a type 2 fuzzy c-means clustering algorithm is proposed. The extension is based on the integration of spatial information in the membership function (MF). The performance of this technique is demonstrated by several experiments on natural textures.

Online publication date: Tue, 21-Oct-2014

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