Automatic learning of image filters using Cartesian genetic programming

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

  author =       "P. C. D. Paris and Emerson Carlos Pedrino and 
                 Maria do Carmo Nicoletti",
  title =        "Automatic learning of image filters using Cartesian
                 genetic programming",
  journal =      "Integrated Computer-Aided Engineering",
  year =         "2015",
  volume =       "22",
  number =       "2",
  pages =        "135--151",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming, CGP-based computational model,
                 mathematical morphology, morphological image filters,
                 automatic construction of image filters",
  bibdate =      "2015-04-24",
  bibsource =    "DBLP,
  DOI =          "doi:10.3233/ICA-150482",
  size =         "17 pages",
  abstract =     "This paper proposes a computational modelling for
                 image filtering processes based on the Cartesian
                 Genetic Programming (CGP) methodology, suitable for
                 hardware devices. A computational system named ALIF-CGP
                 (Automatic Learning of Image Filters Using Cartesian
                 Genetic Programming) was designed as a simulator for
                 automatically constructing a sequence of operators,
                 mainly morphological and logical, which can filter a
                 particular shape of image. ALIF-CGP is a convenient
                 option for executing the non-trivial task, usually
                 manually done by human experts, of selecting the
                 sequence of nonlinear operators to be used in
                 morphological filters. ALIF-CGP has already a built-in
                 pool of morphological and logical operators, which can
                 be used by default. The user, however, has the
                 flexibility of choosing only those operators which are
                 of interest or then, conveniently introduce new ones.
                 The system expects as input a pair of images
                 (input-target). The flexibility given by the CGP-based
                 computational modeling used by ALIF-CGP as well as its
                 efficiency and satisfactory results, obtained in
                 various image processing case studies, recommend its
                 use when developing a hardware implementation for the
                 purposes of image filtering. A few case studies using
                 ALIF-CGP are presented and comparatively analysed in
                 relation to previous results available in the
  notes =        "Matlab",

Genetic Programming entries for Paulo Cesar Donizeti Paris Emerson Carlos Pedrino Maria do Carmo Nicoletti