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Component-Trees and Multi-value Images: A Comparative Study

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Mathematical Morphology and Its Application to Signal and Image Processing (ISMM 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5720))

Abstract

In this article, we discuss the way to derive connected operators based on the component-tree concept and devoted to multi-value images. In order to do so, we first extend the grey-level definition of the component-tree to the multi-value case. Then, we compare some possible strategies for colour image processing based on component-trees in two application fields: colour image filtering and colour document binarisation.

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Author information

Authors and Affiliations

  1. Université Nancy 1, LORIA, UMR CNRS, 7503, France

    Benoît Naegel

  2. Université de Strasbourg, LSIIT, UMR CNRS, 7005, France

    Nicolas Passat

Authors
  1. Benoît Naegel
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  2. Nicolas Passat
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Editor information

Editors and Affiliations

  1. Institute of Mathematics and Computing Science, University of Groningen, P. O. Box 407, 9700, Groningen, AK, The Netherlands

    Michael H. F. Wilkinson

  2. Institute for Mathematics and Computing Science, University of Groningen, P.O. Box 800, 9700, Groningen, AK, The Netherlands

    Jos B. T. M. Roerdink

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Naegel, B., Passat, N. (2009). Component-Trees and Multi-value Images: A Comparative Study. In: Wilkinson, M.H.F., Roerdink, J.B.T.M. (eds) Mathematical Morphology and Its Application to Signal and Image Processing. ISMM 2009. Lecture Notes in Computer Science, vol 5720. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03613-2_24

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  • DOI: https://doi.org/10.1007/978-3-642-03613-2_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03612-5

  • Online ISBN: 978-3-642-03613-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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