• DocumentCode
    3574226
  • Title

    High accuracy optical character recognition algorithms using learning array of ANN

  • Author

    Vani, B. ; Beaulah, M. Shyni ; Deepalakshmi, R.

  • Author_Institution
    Velammal Coll. of Eng. & Technol., CSE, Madurai, India
  • fYear
    2014
  • Firstpage
    1474
  • Lastpage
    1479
  • Abstract
    Optical Character recognition refers to the process of translating the handwritten or printed text into a format that is understood by the machines for the purpose of editing, searching and indexing. The Performance of the current OCR illustrates and explains the actual errors and imaging defects in recognition with illustrated examples. This paper aims to create an application interface for OCR using artificial neural network as a back end to achieve high accurate rate in recognition. The proposed algorithm using neural network concept provides a high accuracy rate in recognition of characters. The proposed approach is implemented and tested on isolated character database consisting of English characters, digits and keyboard special characters.
  • Keywords
    handwritten character recognition; learning (artificial intelligence); neural nets; optical character recognition; ANN; English characters; OCR; artificial neural network; digits; handwritten text; high accuracy optical character recognition algorithms; imaging defects; isolated character database; keyboard special characters; learning array; neural network concept; printed text; Arrays; Artificial neural networks; Character recognition; Computers; Neurons; Optical character recognition software; Artificial Neural Networks; BPN; OCR; image digitization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuit, Power and Computing Technologies (ICCPCT), 2014 International Conference on
  • Print_ISBN
    978-1-4799-2395-3
  • Type

    conf

  • DOI
    10.1109/ICCPCT.2014.7054772
  • Filename
    7054772