A Genetic Programming Approach for Image Segmentation

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

@InCollection{Perlin:2013:CIIP,
  author =       "Hugo Alberto Perlin and Heitor Silverio Lopes",
  title =        "A Genetic Programming Approach for Image
                 Segmentation",
  booktitle =    "Computational Intelligence in Image Processing",
  publisher =    "Springer",
  year =         "2013",
  editor =       "Amitava Chatterjee and Patrick Siarry",
  chapter =      "4",
  pages =        "71--90",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-30620-4",
  DOI =          "doi:10.1007/978-3-642-30621-1_4",
  abstract =     "This work presents a methodology for using genetic
                 programming (GP) for image segmentation. The image
                 segmentation process is seen as a classification
                 problem where some regions of an image are labelled as
                 foreground (object of interest) or background. GP uses
                 a set of terminals and nonterminals, composed by
                 algebraic operations and convolution filters. A
                 function fitness is defined as the difference between
                 the desired segmented image and that obtained by the
                 application of the mask evolved by GP. A penalty term
                 is used to decrease the number of nodes of the tree,
                 minimally affecting the quality of solutions. The
                 proposed approach was applied to five sets of images,
                 each one with different features and objects of
                 interest. Results show that GP was able to evolve
                 solutions of high quality for the problem. Thanks to
                 the penalty term of the fitness function, the solutions
                 found are simple enough to be used and understood by a
                 human user.",
  affiliation =  "Federal Institute of Education, Science and Technology
                 of Parana, Campus Paranagua, Paranagua, Brazil",
}

Genetic Programming entries for Hugo Alberto Perlin Heitor Silverio Lopes

Citations