• DocumentCode
    3499872
  • Title

    Hybrid fitness assignment strategy in IGA

  • Author

    Sugimoto, Futoshi ; Yoneyama, Masahide

  • Author_Institution
    Dept. of Inf. & Comput. Sci., Toyo Univ., Saitama, Japan
  • fYear
    2002
  • fDate
    9-11 Dec. 2002
  • Firstpage
    284
  • Lastpage
    287
  • Abstract
    We have been developing a hybrid fitness assignment strategy to realize a natural interaction in IGA. The strategy allows a user to select some individuals and evaluate a grade that shows how the selected individual resembles a target image. In this paper, we will show a method to compose fitness when a user selects two individuals in the hybrid fitness assignment strategy. It is known that better performance is obtained when two individuals are selected in the generations limited with a condition. The condition is equivalent to the actual situation in which it is difficult for a user to select only one individual. The hybrid strategy is useful to realize a more natural interaction in the actual situation.
  • Keywords
    genetic algorithms; image matching; image retrieval; image sampling; parameter space methods; IGA; human interface; hybrid fitness assignment strategy; individual selection; interactive genetic algorithm; natural interaction; parameter space; target image; Differential equations; Fuzzy reasoning; Genetic algorithms; Humans; Search methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Signal Processing, 2002 IEEE Workshop on
  • Print_ISBN
    0-7803-7713-3
  • Type

    conf

  • DOI
    10.1109/MMSP.2002.1203301
  • Filename
    1203301