A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Pedrino:2011:IJRC,
  author =       "Emerson Carlos Pedrino and Jose Hiroki Saito and 
                 Valentin Obac Roda",
  title =        "A Genetic Programming Approach to Reconfigure a
                 Morphological Image Processing Architecture",
  journal =      "International Journal of Reconfigurable Computing",
  year =         "2011",
  volume =       "2011",
  number =       "Article ID 712494",
  keywords =     "genetic algorithms, genetic programming",
  publisher =    "Hindawi Publishing Corporation",
  ISSN =         "16877195",
  bibsource =    "OAI-PMH server at www.doaj.org",
  language =     "eng",
  oai =          "oai:doaj-articles:eed67a745bb9ae9d853b26e9682e4311",
  URL =          "http://downloads.hindawi.com/journals/ijrc/2011/712494.pdf",
  DOI =          "doi:10.1155/2011/712494",
  size =         "10 pages",
  abstract =     "Mathematical morphology supplies powerful tools for
                 low-level image analysis. Many applications in computer
                 vision require dedicated hardware for real-time
                 execution. The design of morphological operators for a
                 given application is not a trivial one. Genetic
                 programming is a branch of evolutionary computing, and
                 it is consolidating as a promising method for
                 applications of digital image processing. The main
                 objective of genetic programming is to discover how
                 computers can learn to solve problems without being
                 programmed for that. In this paper, the development of
                 an original reconfigurable architecture using logical,
                 arithmetic, and morphological instructions generated
                 automatically by a genetic programming approach is
                 presented. The developed architecture is based on FPGAs
                 and has among the possible applications, automatic
                 image filtering, pattern recognition and emulation of
                 unknown filter. Binary, gray, and colour image
                 practical applications using the developed architecture
                 are presented and the results are compared with similar
                 techniques found in the literature.",
}

Genetic Programming entries for Emerson Carlos Pedrino Jose Hiroki Saito Valentin Obac Roda

Citations