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Image Database Assisted Classification

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Visual Information and Information Systems (VISUAL 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1614))

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Abstract

Image similarity can be defined in a number of different semantic contexts. At the lowest common denominator, images may be classified as similar according to geometric properties, such as color and shape distributions. At the mid-level, a deeper image similarity may be defined according to semantic properties, such as scene content or description. We propose an even higher level of image similarity, in which domain knowledge is used to reason about semantic properties, and similarity is based on the results of reasoning.

At this level, images with only slightly different (or similar) semantic descriptions may be classified as radically different (or similar), based upon the execution of the domain knowledge. For demonstration, we show experiments performed on a small database of 300 images of the retina, classified according to fourteen diagnoses.

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References

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Author information

Authors and Affiliations

  1. Visual Computing Lab, University of California San Diego, San Diego

    Simone Santini, Edd Hunter, Valentina Kouznetsova & Adam Hoover

  2. Intelligent Sensory Information Systems, University of Amsterdam, Amsterdam

    Marcel Worring

  3. Department of Ophthalmology, University of California San Diego, San Diego

    Michael Goldbaum

Authors
  1. Simone Santini
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  2. Marcel Worring
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  3. Edd Hunter
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  4. Valentina Kouznetsova
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  5. Michael Goldbaum
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  6. Adam Hoover
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Editor information

Editors and Affiliations

  1. Computer Science Department, Leiden University, Niels Bohrweg 1, 2333 CA, Leiden, The Netherlands

    Dionysius P. Huijsmans

  2. Research Institute Computer Science, University of Amsterdam, Kruislaan 403, 1098 SJ, Amsterdam, The Netherlands

    Arnold W. M. Smeulders

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© 1999 Springer-Verlag Berlin Heidelberg

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Santini, S., Worring, M., Hunter, E., Kouznetsova, V., Goldbaum, M., Hoover, A. (1999). Image Database Assisted Classification. In: Huijsmans, D.P., Smeulders, A.W.M. (eds) Visual Information and Information Systems. VISUAL 1999. Lecture Notes in Computer Science, vol 1614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48762-X_90

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  • DOI: https://doi.org/10.1007/3-540-48762-X_90

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66079-8

  • Online ISBN: 978-3-540-48762-3

  • eBook Packages: Springer Book Archive

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