• DocumentCode
    2629231
  • Title

    An Arabic character recognition system using neural network

  • Author

    Sanossian, Hermineh Y Y

  • Author_Institution
    Comput. Sci. Dept., Mutah Univ., Karak, Jordan
  • fYear
    1996
  • fDate
    4-6 Sep 1996
  • Firstpage
    340
  • Lastpage
    348
  • Abstract
    An optical character recognition system, which uses a multilayer perceptron classifier, is described. A new approach for the classification of Arabic characters is presented. The technique used is invariant to translation, scale and rotation. Present day artificial neural network (ANN) architecture for invariant character recognition is too complex for our present technology. An alternative procedure is to preprocess the input data and represent them in another form which is invariant to geometrical changes. The advantage of using such a method is that the number of input features is reduced considerably
  • Keywords
    feature extraction; image classification; multilayer perceptrons; optical character recognition; Arabic character recognition system; input features; invariant character recognition; multilayer perceptron classifier; optical character recognition system; Artificial neural networks; Character recognition; Computer science; Data preprocessing; Feature extraction; Multilayer perceptrons; Neural networks; Optical character recognition software; Optical computing; Pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks for Signal Processing [1996] VI. Proceedings of the 1996 IEEE Signal Processing Society Workshop
  • Conference_Location
    Kyoto
  • ISSN
    1089-3555
  • Print_ISBN
    0-7803-3550-3
  • Type

    conf

  • DOI
    10.1109/NNSP.1996.548364
  • Filename
    548364