A new approach for texture classification in CBIR Online publication date: Fri, 16-Jul-2010
by Shengju Sang, Mingxia Liu, Jing Liu, Qi An
International Journal of Computer Applications in Technology (IJCAT), Vol. 38, No. 1/2/3, 2010
Abstract: In the field of Content-Based Image Retrieval (CBIR), the semantic understanding of textures has long been a difficult problem, especially the texture classification. This paper proposes a new approach for texture classification, which adopts ten words describing textures in natural language. Texture features of an image are extracted by Discrete Wavelet Transform (DWT), and then classified through both Back Propagating Neural Network (BPNN) and Support Vector Machine (SVM) classifiers. Experimental results show that this approach of texture classification for natural texture is feasible.
Online publication date: Fri, 16-Jul-2010
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