• DocumentCode
    2673829
  • Title

    Feature extraction technique for Hindi numerals

  • Author

    Sanossian, Hermineh

  • Author_Institution
    Mutah Univ., Karak, Jordan
  • fYear
    1998
  • fDate
    31 Aug-2 Sep 1998
  • Firstpage
    524
  • Lastpage
    530
  • Abstract
    In this paper a feature extraction technique is presented and applied to printed Hindi numerals. Fourteen different fonts with different sizes are used for training and testing. The method uses local information to extract the features. Classification is performed using neural networks. To reduce the percentage of the error rate a number of networks is trained and a voting system is used to obtain the final result
  • Keywords
    character recognition; feature extraction; learning (artificial intelligence); neural nets; pattern classification; Hindi numeral recognition; feature extraction; inverse gradient method; learning; neural networks; pattern classification; voting; Data mining; Error analysis; Feature extraction; Image segmentation; Neural networks; Page description languages; Pattern recognition; Real time systems; Testing; Voting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks for Signal Processing VIII, 1998. Proceedings of the 1998 IEEE Signal Processing Society Workshop
  • Conference_Location
    Cambridge
  • ISSN
    1089-3555
  • Print_ISBN
    0-7803-5060-X
  • Type

    conf

  • DOI
    10.1109/NNSP.1998.710683
  • Filename
    710683