An Evolutionary Framework for Colorimetric Characterization of Scanners

  • Simone Bianco
  • Francesca Gasparini
  • Raimondo Schettini
  • Leonardo Vanneschi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4974)


In this work we present an evolutionary framework for colorimetric characterization of scanners. The problem consists in finding a mapping from the RGB space (where points indicate how a color stimulus is produced by a given device) to their corresponding values in the CIELAB space (where points indicate how the color is perceived in standard, i.e. device independent, viewing conditions). The proposed framework is composed by two phases: in the first one we use genetic programming for assessing a characterizing polynomial; in the second one we use genetic algorithms to assess suitable coefficients of that polynomial. Experimental results are reported to confirm the effectiveness of our framework with respect to a set of methods in the state of the art.


Evolutionary Framework Color Patch Total Little Square Characterization Problem Color Scanner 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Simone Bianco
    • 1
  • Francesca Gasparini
    • 1
  • Raimondo Schettini
    • 1
  • Leonardo Vanneschi
    • 1
  1. 1.Dipartimento di Informatica, Sistemistica e ComunicazioneUniversity of Milano-BicoccaMilanItaly

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