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Proceedings of the 2nd International Symposium on Web Information Systems and Applications (WISA 2009)

Nanchang, China, May 22-24, 2009

Editors: Fei Yu, Jiexian Zeng, and Guangxue Yue

AP Catalog Number: AP-PROC-CS-09CN001

ISBN: 978-952-5726-00-8 (Print), 978-952-5726-01-5 (CD-ROM)

Page(s): 238-241

Combining Perceptual Texture Features and Gabor Wavelet Features for Texture Image Classification

           Muwei Jian, Lei Liu, Cheng Yin, Lin Yuan

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Abstract

As a special class of images, texture can represent the surface characteristics of one object, e.g. terrain, vegetation, mineral and fur, etc. This paper combines perceptual texture features and wavelet features for texture image classification. Three new texture features which are proved to be in accordance with human visual perception are introduced. These features include directionality, contrast and coarseness in wavelet domain. The proposed scheme have a advantage that all the texture features are derived from wavelet transform, and it can reduce the  time complexity of  texture features extraction. We test our proposed method using the Brodatz texture database, and the experimental results show the scheme has produced promising results.

Index Terms

perceptual texture features; wavelet features; texture image classification

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