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Texture Feature-Based Image Classification Using Wavelet Package Transform

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Advances in Intelligent Computing (ICIC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3644))

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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.

This work was supported by the National Science Foundation of China (Nos.60472111 and 60405002).

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Authors and Affiliations

  1. Institute of Intelligent Machines, Chinese Academy of Sciences, P.O.Box 1130, Hefei, Anhui, 230031, China

    Yue Zhang, Xing-Jian He & Jun-Hua Han

Authors
  1. Yue Zhang
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  2. Xing-Jian He
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  3. Jun-Hua Han
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Editor information

Editors and Affiliations

  1. Intelligent Computing Lab, Institute of Intelligent Machines, Chinese Academy of Sciences,, China

    De-Shuang Huang

  2. School of Computer & Information Technology, Beijing Jiaotong University, 100044, Beijing, P.R. China

    Xiao-Ping Zhang

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, P.O. Box, Singapore

    Guang-Bin Huang

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© 2005 Springer-Verlag Berlin Heidelberg

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Zhang, Y., He, XJ., Han, JH. (2005). Texture Feature-Based Image Classification Using Wavelet Package Transform. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538059_18

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  • DOI: https://doi.org/10.1007/11538059_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28226-6

  • Online ISBN: 978-3-540-31902-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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