• DocumentCode
    2613728
  • Title

    Character recognition using neural based feature extractor and classifier

  • Author

    Cao, J. ; Ahmadi, M. ; Shridhar, M.

  • Author_Institution
    Dept. of Electr. Eng., Windsor Univ., Ont., Canada
  • fYear
    1993
  • fDate
    3-6 May 1993
  • Firstpage
    2442
  • Abstract
    The authors present a neural network architecture for the recognition of handwritten digits and machine printed multi-font characters. To reduce the dimension of the input data vector as well as robustness of the system, an appropriate neural net is utilized for the feature extraction part which is cascaded with another neural net for the classification purpose. The proposed architecture has been tested on a large sample of real field data and the results indicate the effectiveness of the proposed technique
  • Keywords
    character recognition; character sets; feature extraction; neural nets; pattern classification; classification; handwritten digits; input data vector; machine printed multi-font characters; neural based feature extractor; neural network architecture; robustness; Character recognition; Computer architecture; Data mining; Feature extraction; Handwriting recognition; Neural networks; Personal communication networks; Principal component analysis; Robustness; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    0-7803-1281-3
  • Type

    conf

  • DOI
    10.1109/ISCAS.1993.394258
  • Filename
    394258