Automatic Construction of Gaussian-Based Edge Detectors Using Genetic Programming

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

@InProceedings{Fu:evoapps13a,
  author =       "Wenlong Fu and Mark Johnston and Mengjie Zhang",
  title =        "Automatic Construction of Gaussian-Based Edge
                 Detectors Using Genetic Programming",
  booktitle =    "Applications of Evolutionary Computing,
                 EvoApplications 2013: EvoCOMNET, EvoCOMPLEX, EvoENERGY,
                 EvoFIN, EvoGAMES, EvoIASP, EvoINDUSTRY, EvoNUM, EvoPAR,
                 EvoRISK, EvoROBOT, EvoSTOC",
  year =         "2013",
  month =        "3-5 " # apr,
  editor =       "Anna I. Esparcia-Alcazar and Antonio Della Cioppa and 
                 Ivanoe {De Falco} and Ernesto Tarantino and 
                 Carlos Cotta and Robert Schaefer and Konrad Diwold and 
                 Kyrre Glette and Andrea Tettamanzi and 
                 Alexandros Agapitos and Paolo Burrelli and J. J. Merelo and 
                 Stefano Cagnoni and Mengjie Zhang and Neil Urquhart and Kevin Sim and 
                 Aniko Ekart and Francisco {Fernandez de Vega} and 
                 Sara Silva and Evert Haasdijk and Gusz Eiben and 
                 Anabela Simoes and Philipp Rohlfshagen",
  series =       "LNCS",
  volume =       "7835",
  publisher =    "Springer Verlag",
  address =      "Vienna",
  publisher_address = "Berlin",
  pages =        "365--375",
  organisation = "EvoStar",
  keywords =     "genetic algorithms, genetic programming, Edge
                 Detection, Gaussian Filter",
  isbn13 =       "978-3-642-37191-2",
  DOI =          "doi:10.1007/978-3-642-37192-9_37",
  size =         "11 pages",
  abstract =     "Gaussian-based edge detectors have been developed for
                 many years, but there are still problems with how to
                 set scales for Gaussian filters and how to combine
                 Gaussian filters. In order to address both problems, a
                 Genetic Programming (GP) system is proposed to
                 automatically choose scales for Gaussian filters and
                 automatically combine Gaussian filters. In this study,
                 the GP system is used to construct rotation invariant
                 Gaussian-based edge detectors based on a benchmark
                 image dataset. The experimental results show that the
                 GP evolved Gaussian-based edge detectors are better
                 than the Gaussian gradient and rotation invariant
                 surround suppression to extract edge features.",
  notes =        "http://www.kevinsim.co.uk/evostar2013/cfpEvoApplications.html
                 EvoApplications2013 held in conjunction with
                 EuroGP2013, EvoCOP2013, EvoBio'2013 and EvoMusArt2013",
}

Genetic Programming entries for Wenlong Fu Mark Johnston Mengjie Zhang

Citations