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Industrial Conference on Data Mining

ICDM 2004: Advances in Data Mining pp 60–68Cite as

Mining Images to Find General Forms of Biological Objects

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3275))

Abstract

We propose and evaluate a method for the recognition of airborne fungi spores. We suggest a case-based object-recognition method to identify spores in a digital microscopic image. We do not use the gray values of the case, but the object edges instead. The similarity measure measures the average angle between the vectors of the template and the object. Case generation is done semi-automatically by manually tracing the object, automatic shape alignment, similarity calculation, clustering, and prototype calculation.

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References

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Author information

Authors and Affiliations

  1. IBaI, Institute of Computer Vision and applied Computer Sciences, Körnerstr 10, 04107, Leipzig, Germany

    Petra Perner, Horst Perner, Angela Bühring & Silke Jänichen

Authors
  1. Petra Perner
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  2. Horst Perner
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  3. Angela Bühring
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  4. Silke Jänichen
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Editor information

Editors and Affiliations

  1. Institute of Computer Vision and applied Computer Sciences, IBaI, Germany

    Petra Perner

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© 2004 Springer-Verlag Berlin Heidelberg

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Perner, P., Perner, H., Bühring, A., Jänichen, S. (2004). Mining Images to Find General Forms of Biological Objects. In: Perner, P. (eds) Advances in Data Mining. ICDM 2004. Lecture Notes in Computer Science(), vol 3275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30185-1_7

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  • DOI: https://doi.org/10.1007/978-3-540-30185-1_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24054-9

  • Online ISBN: 978-3-540-30185-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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