• DocumentCode
    3487712
  • Title

    A color palette reduction method using multiobjective evolutionary clustering algorithm

  • Author

    Sadohira, Motonari ; Saito, Akio ; Aguirre, Hernan ; Tanaka, Kiyoshi

  • Author_Institution
    Fac. of Eng., Shinshu Univ., Nagano, Japan
  • fYear
    2011
  • fDate
    23-26 Aug. 2011
  • Firstpage
    238
  • Lastpage
    243
  • Abstract
    When we display color images on low devices having a limited number of pixels and/or colors, the technique called “color palette reduction” which reduces the colors in color palette to represent the input image with a limited number of colors is often used. In the color reduction process, we should select representative colors by considering color distribution of the input image so that the error between the approximated image and the original one becomes minimum. In this work, we try to use a new clustering approach called MOCK [1], which uses multi-objective evolutionary algorithm as the mean of clustering, and verify the basic performance of the proposed approach through computer simulation using several benchmark color images.
  • Keywords
    approximation theory; evolutionary computation; image colour analysis; image representation; pattern clustering; MOCK clustering approach; color distribution; color images; color palette reduction method; image approximation; multiobjective evolutionary clustering algorithm; representative color; Benchmark testing; Clustering algorithms; Color; Data models; IP networks; Image color analysis; Mathematical model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Computers and Signal Processing (PacRim), 2011 IEEE Pacific Rim Conference on
  • Conference_Location
    Victoria, BC
  • ISSN
    1555-5798
  • Print_ISBN
    978-1-4577-0252-5
  • Electronic_ISBN
    1555-5798
  • Type

    conf

  • DOI
    10.1109/PACRIM.2011.6032899
  • Filename
    6032899