A new approach for texture classification in CBIR. (19th July 2010)

• Record Type: Journal Article
• Authors: Sang, Shengju; Liu, Mingxia; Liu, Jing; An, Qi
• Is Part Of: International journal of computer applications technology. Volume 38:Number 1-3(2010)
• Page Start: 34
• Page End: 39
• Publication Date: 2010-07-19
• Subjects: CBIR -- content-based image retrieval -- texture classification -- DWT -- discrete wavelet transforms -- BPNN -- back propagation neural networks -- SVM -- support vector machines -- WPT -- wavelet package transforms -- natural language -- texture features -- image processing; Technology -- Data processing -- Periodicals; 620.00285
• Languages: English
• ISSNs: 0952-8091

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.