• DocumentCode
    2462206
  • Title

    Resolution of the Inverse Problem for Iterated Function Systems using Evolutionary Algorithms

  • Author

    Sarafopoulos, Anargyros ; Buxton, Bernard

  • Author_Institution
    Bournemouth Univ., Poole
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1071
  • Lastpage
    1078
  • Abstract
    The resolution of the inverse problem for iterated function systems (IFS) is a problem that has remained open, currently there is no general solution that requires no human interaction and provides optimal results. Here we present a novel approach to the resolution of the general inverse problem for IFS using segmentation of target images in conjuction with an Evolutionary Algorithm that is a Genetic Programming-Evolutionary Strategies hybrid.
  • Keywords
    genetic algorithms; image segmentation; inverse problems; evolutionary algorithms; genetic programming; inverse problem; iterated function systems; target images segmentation; Animation; Evolutionary computation; Fractals; Genetics; Humans; Image coding; Image resolution; Image segmentation; Inverse problems; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9487-9
  • Type

    conf

  • DOI
    10.1109/CEC.2006.1688428
  • Filename
    1688428
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2462206