• DocumentCode
    2953911
  • Title

    Image Matching Using Genetic Algorithm on GPU

  • Author

    Ke, Yongzhen ; Li, Yuhao ; Li, Dandan

  • Author_Institution
    Sch. of Comput. Sci. & Software, Tianjin Polytech. Univ., Tianjin, China
  • fYear
    2011
  • fDate
    30-31 July 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Genetic algorithm is widely applied to the field of image matching. But it is very time-consuming to solve some large computational problems with large search space or complex fitness function. Image matching using genetic algorithm has not achieved real-time performance. An improved genetic algorithm based on CUDA with full use of GPU´s parallelism was presented in this paper. The experimental results show that improved genetic algorithm on GPU has an excellent performance on acceleration of image marching. Now the GPU supporting CUDA is very popular in personal computer. So the proposed algorithm can be easy to apply other field.
  • Keywords
    computer graphic equipment; genetic algorithms; image matching; microcomputers; parallel architectures; CUDA; GPU parallelism; genetic algorithm; image matching; personal computer; Biological cells; Computational modeling; Genetic algorithms; Graphics processing unit; Image matching; Instruction sets; Parallel processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation and Systems Engineering (CASE), 2011 International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4577-0859-6
  • Type

    conf

  • DOI
    10.1109/ICCASE.2011.5997657
  • Filename
    5997657