Morphological algorithm design for binary images using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Marcos I. Quintana and Riccardo Poli and 
                 Ela Claridge",
  title =        "Morphological algorithm design for binary images using
                 genetic programming",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2006",
  volume =       "7",
  number =       "1",
  pages =        "81--102",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming, Mathematical
                 morphology, Image analysis, memory",
  ISSN =         "1389-2576",
  URL =          "",
  DOI =          "doi:10.1007/s10710-006-7012-3",
  size =         "22 pages",
  abstract =     "a Genetic Programming (GP) approach to the design of
                 Mathematical Morphology (MM) algorithms for binary
                 images. The algorithms are constructed using logic
                 operators and the basic MM operators, i.e. erosion and
                 dilation, with a variety of structuring elements. GP is
                 used to evolve MM algorithms that convert a binary
                 image into another containing just a particular feature
                 of interest. In the study we have tested three fitness
                 functions, training sets with different numbers of
                 elements, training images of different sizes, and 7
                 different features in two different kinds of
                 applications. The results obtained show that it is
                 possible to evolve good MM algorithms using GP.",
  notes =        "Store operation used only in first part. lilgp. Linux
                 cluster. irregular kernels. Music score OCR.",

Genetic Programming entries for Marcos Ivan Quintana-Hernandez Riccardo Poli Ela Claridge