• DocumentCode
    3166575
  • Title

    A neuro-fuzzy approach to recognize Arabic handwritten characters

  • Author

    Alimi, Adel M.

  • Author_Institution
    Dept. of Electr. Eng., Ecole Nationale d´´Ingenieurs de Sfax, Tunisia
  • Volume
    3
  • fYear
    1997
  • fDate
    9-12 Jun 1997
  • Firstpage
    1397
  • Abstract
    In this paper we describe a system that recognizes online Arabic handwritten characters. In this system, a fuzzy neural network is used to classify characters. The characters used in this system were segmented from cursive handwriting that are modelled by a theory of movement generation. Based on this theory, the features extracted from each character are the neuro-physiological parameters of the equation describing the curvilinear velocity of the script. For each character presented to the system, a fuzzy membership is assigned to each output of the neural network
  • Keywords
    character recognition; feature extraction; fuzzy neural nets; real-time systems; Arabic handwritten character recognition; cursive handwriting; curvilinear velocity; feature extraction; fuzzy membership; fuzzy neural network; online character recognition; segmentation; Character generation; Character recognition; Equations; Feature extraction; Fuzzy neural networks; Handwriting recognition; Neural networks; Pattern recognition; Shape; Tail;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks,1997., International Conference on
  • Conference_Location
    Houston, TX
  • Print_ISBN
    0-7803-4122-8
  • Type

    conf

  • DOI
    10.1109/ICNN.1997.613998
  • Filename
    613998
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3166575