• DocumentCode
    1990412
  • Title

    Arabic character recognition using particle swarm optimization with selected and weighted moment invariants

  • Author

    Sarfraz, Muhammad ; Al-Awami, Ali Taleb Ali

  • Author_Institution
    Dept. of Inf. & Comput. Sci., King Fahd Univ. of Pet. & Miner., Dhahran
  • fYear
    2007
  • fDate
    12-15 Feb. 2007
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A new Arabic character recognition system has been proposed using moments as features. The proposed scheme works in such a way that the features are selected as well as weighted using a swarm-based optimization technique. For the sake of simplicity, it has been assumed that the Arabic text has already been preprocessed and segmented. Recognition results have been achieved up to 82% of accuracy. Authors believe that the 82% of accuracy is mainly due to not using very effective segmentation technique, otherwise the results could be above 95% as has been observed in the case of object recognition in an earlier paper of the authors.
  • Keywords
    character recognition; image segmentation; particle swarm optimisation; Arabic character recognition; Arabic text; particle swarm optimization; swarm-based optimization technique; weighted moment invariants; Character recognition; Computer science; Face detection; Feature extraction; Minerals; Object recognition; Particle swarm optimization; Petroleum; Shape; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on
  • Conference_Location
    Sharjah
  • Print_ISBN
    978-1-4244-0778-1
  • Electronic_ISBN
    978-1-4244-1779-8
  • Type

    conf

  • DOI
    10.1109/ISSPA.2007.4555582
  • Filename
    4555582