Texture feature-based image classification using wavelet package transform

Authors:
Yue Zhang;Xing-Jian He;Jun-Hua Han
Affiliations:
Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China;Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China;Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China
Venue:
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Year:
2005

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Abstract

In this paper, a new method based on wavelet package transform is proposed for classification of texture images. It has been demonstrated that a large amount of texture information of texture images is located in middle-high frequency parts of image, a corresponding method called wavelet package transform, not only decomposing image from the low frequency parts, but also from the middle-high frequency parts, is presented to segment texture images into a few texture domains used for image classification. Some experimental results are obtained to indicate that our method for image classification is superior to the co-occurrence matrix technique obviously.