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Color Deconvolution and Support Vector Machines

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Computational Forensics (IWCF 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5718))

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Abstract

Methods for machine learning (support vector machines) and image processing (color deconvolution) are combined in this paper for the purpose of separating colors in images of documents. After determining the background color, samples from the image that are representative of the colors to be separated are mapped to a feature space. Given the clusters of samples of either color the support vector machine (SVM) method is used to find an optimal separating line between the clusters in feature space. Deconvolution image processing parameters are determined from the separating line. A number of examples of applications in forensic casework are presented.

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References

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Author information

Authors and Affiliations

  1. Netherlands Forensic Institute, The Hague, The Netherlands

    Charles E. H. Berger & Cor J. Veenman

  2. Intelligent Systems Lab, University of Amsterdam, Amsterdam, The Netherlands

    Cor J. Veenman

Authors
  1. Charles E. H. Berger
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  2. Cor J. Veenman
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Editor information

Editors and Affiliations

  1. Netherlands Forensic Institute, The Hague, The Netherlands

    Zeno J. M. H. Geradts

  2. Norwegian Information Security Laboratory, Gjøvik University College, Norway

    Katrin Y. Franke

  3. Digital Technology & Biometrics Department, Netherlands Forensic Institute, The Hague, The Netherlands

    Cor J. Veenman

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© 2009 Springer-Verlag Berlin Heidelberg

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Berger, C.E.H., Veenman, C.J. (2009). Color Deconvolution and Support Vector Machines. In: Geradts, Z.J.M.H., Franke, K.Y., Veenman, C.J. (eds) Computational Forensics. IWCF 2009. Lecture Notes in Computer Science, vol 5718. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03521-0_16

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  • DOI: https://doi.org/10.1007/978-3-642-03521-0_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03520-3

  • Online ISBN: 978-3-642-03521-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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