• DocumentCode
    3309401
  • Title

    Fractal Image Compression Using Genetic Algorithm

  • Author

    Bobde, Sarika Sanjay ; Kulkarni, M.V. ; Kulkarni, P.V.

  • Author_Institution
    Dept. of Comput. Eng., Univ. of Pune, Pune, India
  • fYear
    2010
  • fDate
    20-21 June 2010
  • Firstpage
    241
  • Lastpage
    243
  • Abstract
    This paper gives the improved method of generating a binary image IFS using Genetic Algorithm. To find the maps of IFSs that can encode black and white (BW) images, the Genetic Algorithm uses a variable-length genotype representation, i.e., each IFS is represented as a list of maps, and a map is represented as a set of real parameters. Special genetic operators that maintain and control the feasibility of the individuals in the population are adopted. A fitness function is defined that measures the similarity between the attractor and the image that penalizes a large number of maps and high contractivity factors.
  • Keywords
    Biological cells; Evolutionary computation; Extraterrestrial measurements; Fractals; Genetic algorithms; Genetic engineering; Image coding; Image generation; Image segmentation; Wavelet domain; Fractal Image Compression; Genetic Algorithm; Iterated Function System;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Computer Engineering (ACE), 2010 International Conference on
  • Conference_Location
    Bangalore, Karnataka, India
  • Print_ISBN
    978-1-4244-7154-6
  • Type

    conf

  • DOI
    10.1109/ACE.2010.9
  • Filename
    5532835