Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/16528
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: Texture Recognition by Fusion of Optimized Moment Based and Gabor Energy Features
Author(s): Qaiser, Naeem
Hussain, Mutawarra
Hussain, Amir
Qaiser, Nadeem
Contact Email: amir.hussain@stir.ac.uk
Keywords: Moment based texture features
Gabor energy features
Texture classification
Fisher’s criterion Texture Segmentation
Fusion
Issue Date: Feb-2008
Date Deposited: 26-Aug-2013
Citation: Qaiser N, Hussain M, Hussain A & Qaiser N (2008) Texture Recognition by Fusion of Optimized Moment Based and Gabor Energy Features. International Journal of Computer Science and Network Security, 8 (2), pp. 262-270. http://paper.ijcsns.org/07_book/200802/20080236.pdf
Abstract: Use of a single technique for the extraction of diverse features in a texture image usually shows limited capabilities for texture description. Texture features extracted using different techniques can be merged in an attempt to enhance their texture description capability. This paper explores the fusion of optimized moment and Gabor energy texture features. The Fisher linear discriminant analysis is used to show that the discrimination effectiveness of the features increases as a result of the proposed fusion. Preliminary simulation results have been validated experimentally through the classification and segmentation of real texture images.
URL: http://paper.ijcsns.org/07_book/200802/20080236.pdf
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