• DocumentCode
    604596
  • Title

    An efficient handwritten Devnagari character recognition system using neural network

  • Author

    Sahu, Nilkanta ; Raman, N.K.

  • Author_Institution
    Comput. Sci. Dept., ITM Univ., Gurgaon, India
  • fYear
    2013
  • fDate
    22-23 March 2013
  • Firstpage
    173
  • Lastpage
    177
  • Abstract
    Character recognition systems for various languages and script has gain importance in recent decades and is the area of deep interest for many researchers. Their development is strongly integerated with Neural Networks. But, recognizing Devanagari Script is relatively greater challenge due to script´s complexity. Various techniques have been implemented for this problem with many improvements so far. This paper describes the development and implementation of one such system comprising combination of several stages. Mainly Artificial Neural Network technique is used to designed to preprocess, segment and recognize devanagari characters. The system was designed, implemented, trained and found to exhibit an accuracy of 75.6% on noisy characters.
  • Keywords
    backpropagation; feature extraction; graphical user interfaces; handwritten character recognition; image segmentation; natural language processing; neural nets; optical character recognition; Devanagari character preprocess; Devanagari character segmentation; Devanagari script recognition; GUI; OCR; artificial neural network technique; back propagation neural network; feature extraction; handwritten Devnagari character recognition system; script complexity; Accuracy; Biological neural networks; Character recognition; Feature extraction; Image segmentation; Training; Devnagari Character Recognition; Feature Extraction; OCR; Off-line Handwriting Recognition; Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation, Computing, Communication, Control and Compressed Sensing (iMac4s), 2013 International Multi-Conference on
  • Conference_Location
    Kottayam
  • Print_ISBN
    978-1-4673-5089-1
  • Type

    conf

  • DOI
    10.1109/iMac4s.2013.6526403
  • Filename
    6526403