• DocumentCode
    2198629
  • Title

    Feature Extraction for Online Farsi Characters

  • Author

    Ghods, Vahid ; Kabir, Ehsanollah

  • Author_Institution
    Dept. of Electr. Eng., Islamic Azad Univ., Semnan, Iran
  • fYear
    2010
  • fDate
    16-18 Nov. 2010
  • Firstpage
    477
  • Lastpage
    482
  • Abstract
    This paper demonstrates the effectiveness of proper and efficient features for classifying online Farsi characters. We use these features to classify the main body of Farsi letters to nine groups. We implemented our method on the main bodies of 4000 isolated letters from "TMU dataset". Correct recognition rates of 99% and 94% were achieved for training and test sets respectively.
  • Keywords
    Internet; character recognition; feature extraction; image classification; natural languages; TMU dataset; character recognition; feature extraction; online Farsi character classification; Arabic; Character recognition; Decision tree; Farsi; Feature extraction; Online handwriting; Persian;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Frontiers in Handwriting Recognition (ICFHR), 2010 International Conference on
  • Conference_Location
    Kolkata
  • Print_ISBN
    978-1-4244-8353-2
  • Type

    conf

  • DOI
    10.1109/ICFHR.2010.81
  • Filename
    5693609
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2198629