• DocumentCode
    2145445
  • Title

    Digit/Symbol Pruning and Verification for Arabic Handwritten Digit/Symbol Spotting

  • Author

    Nobile, Nicola ; He, Chun Lei ; Sagheer, Malik Waqas ; Lam, Louisa ; Suen, Ching Y.

  • Author_Institution
    Comput. Sci. & Software Eng. Dept., Concordia Univ., Montreal, QC, Canada
  • fYear
    2011
  • fDate
    18-21 Sept. 2011
  • Firstpage
    648
  • Lastpage
    652
  • Abstract
    In order to spot the digits in a handwritten document, each component is sent to a classifier. This is a time consuming process because a document usually contains several hundred components. A method is presented to reduce the number of candidate components from a handwritten document sent to the classifier. Furthermore, since the classifier does not contain a rejection class, this led to several misclassifications. To lessen this, a verification post processing module was developed in order to reject some false positives. We reached an overall precision of 80% and 83.3% recall on our test set of handwritten documents.
  • Keywords
    document image processing; image classification; Arabic handwritten digit verification; Arabic symbol spotting; classifier; digit-symbol pruning; handwritten document; verification post processing module; Covariance matrix; Databases; Feature extraction; Handwriting recognition; Helium; Skeleton; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2011 International Conference on
  • Conference_Location
    Beijing
  • ISSN
    1520-5363
  • Print_ISBN
    978-1-4577-1350-7
  • Electronic_ISBN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2011.136
  • Filename
    6065391