• DocumentCode
    1783968
  • Title

    Evaluation of genetic algorithm for interactive evolutionary face image beautifying system

  • Author

    Oinuma, Juri ; Arakawa, Kazuki ; Harashima, Hiroshi

  • fYear
    2014
  • fDate
    21-23 May 2014
  • Firstpage
    594
  • Lastpage
    597
  • Abstract
    The performance of a genetic algorithm (GA) with a new way of crossover proposed by authors before is evaluated quantitatively to verify its advantage. This new algorithm was proposed for interactive evolutionary face image beautifying system implemented on a small mobile device. Since the display size is small, GA must work effectively for a very small population size. The new crossover adopts internally and externally dividing and was highly evaluated subjectively by questionnaires. In order to clarify the advantage of the new algorithm, the performance is evaluated by the mean square error between the output face image and the desired face image obtained by modifying the original face image with a graphical tool. The result shows that the performance of the new algorithm is higher than the conventional methods for GA.
  • Keywords
    genetic algorithms; image processing; mean square error methods; GA; crossover; genetic algorithm; graphical tool; interactive evolutionary face image beautifying system; mean square error; mobile device; performance evaluation; Cost function; Face; Genetic algorithms; IEC; Skin; Sociology; Statistics; Interactive evolutionary computing; crossover; face image beautification; genetic algorithm; quantitative evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Control and Signal Processing (ISCCSP), 2014 6th International Symposium on
  • Conference_Location
    Athens
  • Type

    conf

  • DOI
    10.1109/ISCCSP.2014.6877945
  • Filename
    6877945