Color Constancy Algorithm Selection Using CART

  • Simone Bianco
  • Gianluigi Ciocca
  • Claudio Cusano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5646)


In this work, we investigate how illuminant estimation techniques can be improved taking into account intrinsic, low level properties of the images. We show how these properties can be used to drive, given a set of illuminant estimation algorithms, the selection of the best algorithm for a given image. The selection is made by a decision forest composed by several trees that vote for one of the illuminant estimation algorithm. The most voted algorithm is then applied to the input image. Experimental results on the widely used Ciurea and Funt dataset demonstrate the accuracy of our approach in comparison to other algorithms in the state of the art.


Good Algorithm Angular Error Pattern Search Method Pattern Search Algorithm Minkowski Norm 
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 2009

Authors and Affiliations

  • Simone Bianco
    • 1
  • Gianluigi Ciocca
    • 1
  • Claudio Cusano
    • 1
  1. 1.DISCo (Dipartimento di Informatica, Sistemistica e Comunicazione)Università degli Studi di Milano-BicoccaMilanoItaly

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