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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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. https://doi.org/10.1007/978-3-642-15907-7_16
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DOI: https://doi.org/10.1007/978-3-642-15907-7_16
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