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Scene Classification Using Adaptive Processing of Tree Representation of Rectangular-Shape Partition of Images

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3497))

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Abstract

Image classification is very helpful for organizing large image databases and content based image retrieval (CBIR). However, it is very complex and challenging because of lacking effective methods. In this paper, we present a tree representation of images based on rectangular-shape partition. Then an adaptive processing algorithm is adopted to perform the classification task. Experimental results on seven categories of scenery images show that the structural representations are better than the traditional methods and our previous work based on quadtree representation of fixed partition.

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References

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Author information

Authors and Affiliations

  1. Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China

    Wei Sun, Ken Lo & Zheru Chi

Authors
  1. Wei Sun
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  2. Ken Lo
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  3. Zheru Chi
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiao-Feng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Sun, W., Lo, K., Chi, Z. (2005). Scene Classification Using Adaptive Processing of Tree Representation of Rectangular-Shape Partition of Images. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_44

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  • DOI: https://doi.org/10.1007/11427445_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25913-8

  • Online ISBN: 978-3-540-32067-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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