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International Conference on Intelligent Data Engineering and Automated Learning

IDEAL 2008: Intelligent Data Engineering and Automated Learning – IDEAL 2008 pp 459–463Cite as

Feature Locations in Images

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5326))

Abstract

We review the recent technique of two dimensional canonical correlation analysis and illustrate its use as a method for identification of the location of particular features in a data set.

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References

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Author information

Authors and Affiliations

  1. Intelligent Signal Processing Lab, Korea University, Korea

    Hokun Kim & Hanseok Ko

  2. School of Computing, University of the West of Scotland, UK

    Colin Fyfe

Authors
  1. Hokun Kim
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  2. Colin Fyfe
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  3. Hanseok Ko
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Editor information

Editors and Affiliations

  1. University of West Scotland, PA1 2BE, Paisley, Scotland

    Colin Fyfe

  2. KAIST, Daejeon, Korea

    Dongsup Kim

  3. Brain Science Research Center and Department of Bio & Brain Engineering, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, 305-701, Daejeon, Korea

    Soo-Young Lee

  4. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2008 Springer-Verlag Berlin Heidelberg

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Cite this paper

Kim, H., Fyfe, C., Ko, H. (2008). Feature Locations in Images. In: Fyfe, C., Kim, D., Lee, SY., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2008. IDEAL 2008. Lecture Notes in Computer Science, vol 5326. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88906-9_58

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  • DOI: https://doi.org/10.1007/978-3-540-88906-9_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88905-2

  • Online ISBN: 978-3-540-88906-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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