Evolving color constancy

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Ebner:2006:PRL,
  author =       "Marc Ebner",
  title =        "Evolving color constancy",
  journal =      "Pattern Recognition Letters",
  year =         "2006",
  volume =       "27",
  number =       "11",
  pages =        "1220--1229",
  month =        aug,
  note =         "Evolutionary Computer Vision and Image Understanding",
  keywords =     "genetic algorithms, genetic programming, Colour
                 constancy, Local space average colour",
  DOI =          "doi:10.1016/j.patrec.2005.07.020",
  abstract =     "The ability to compute colour constant descriptors of
                 objects in view irrespective of the light illuminating
                 the scene is called color constancy. We have used
                 genetic programming to evolve an algorithm for colour
                 constancy. The algorithm runs on a grid of processing
                 elements. Each processing element is connected to
                 neighbouring processing elements. Information exchange
                 can therefore only occur locally. Randomly generated
                 colour Mondrians were used as test cases. The evolved
                 individual was tested on synthetic as well as real
                 input images. Encouraged by these results we developed
                 a parallel algorithm for colour constancy. This
                 algorithm is based on the computation of local space
                 average colour. Local space average colour is used to
                 estimate the illuminant locally for each image pixel.
                 Given an estimate of the illuminant, we can compute the
                 reflectances of the corresponding object points. The
                 algorithm can be easily mapped to a neural architecture
                 and could be implemented directly in CCD or CMOS chips
                 used in todays cameras.",
}

Genetic Programming entries for Marc Ebner

Citations