• DocumentCode
    2989736
  • Title

    Multifont Ottoman character recognition

  • Author

    Öztürk, Ali ; Günes, Salih ; Özbay, Yüksel

  • Author_Institution
    Comput. Center, Bilkent Univ., Ankara, Turkey
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    945
  • Abstract
    Ottoman characters from three different fonts are used in character recognition problems; broadly speaking, this involves transferring a page that contain symbols to the computer and matching these symbols with previously known or recognized symbols after extraction the features of these symbols via appropriate preprocessing methods. Because of silent features of the characters implementing an Ottoman character recognition system is difficult work. Different researchers have done lots of works for years to develop systems that would recognize Latin characters. Although almost one million people use Ottoman characters, many with different native languages, the number of studies in this field is insufficient. In this study 25 different machine-printed characters were used to train the Artificial Neural Network and a 95% classification accuracy for the characters in these fonts and a 70% classification accuracy for a different font have been found
  • Keywords
    handwritten character recognition; pattern classification; character recognition; classification accuracy; multifont Ottoman character; preprocessing methods; symbols; Backpropagation; Character recognition; Feature extraction; LAN interconnection; Multi-layer neural network; Neural networks; Shape; Table lookup; Text analysis; Text recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics, Circuits and Systems, 2000. ICECS 2000. The 7th IEEE International Conference on
  • Conference_Location
    Jounieh
  • Print_ISBN
    0-7803-6542-9
  • Type

    conf

  • DOI
    10.1109/ICECS.2000.913032
  • Filename
    913032