Spectrum Evaluation on Multispectral Images by Machine Learning Techniques

  • Marcin Michalak
  • Adam Świtoński
Conference paper

DOI: 10.1007/978-3-642-15907-7_16

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6375)
Cite this paper as:
Michalak M., Świtoński A. (2010) Spectrum Evaluation on Multispectral Images by Machine Learning Techniques. In: Bolc L., Tadeusiewicz R., Chmielewski L.J., Wojciechowski K. (eds) Computer Vision and Graphics. ICCVG 2010. Lecture Notes in Computer Science, vol 6375. Springer, Berlin, Heidelberg

Abstract

Multispectral pictures of skin are considered as the way of detection of regions with tumor. This article raises the problem of postprocessing of the color spectrum for the improvement of the tumor region detection accuracy. As the reference point spectra of 24 model colors were aquisited and then compared with their original spectra. Difference betweeen the original and aquisited spectra motivated the authors to use data mining nonparametrical techniques to find the measured spectra postprocessing technique. Two different approaches are described: classificational and regressional.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Marcin Michalak
    • 1
    • 3
  • Adam Świtoński
    • 2
    • 3
  1. 1.Central Mining InstituteKatowicePoland
  2. 2.Polish-Japanese Institute of Information TechnologyBytomPoland
  3. 3.Silesian University of TechnologyGliwicePoland

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