• DocumentCode
    1640809
  • Title

    ICDAR 2009 Handwritten Farsi/Arabic Character Recognition Competition

  • Author

    Mozaffari, Saeed ; Soltanizadeh, Hadi

  • Author_Institution
    Electr. & Comput. Eng. Dept., Semana Univ., Semnan, Iran
  • fYear
    2009
  • Firstpage
    1413
  • Lastpage
    1417
  • Abstract
    In recent years, the recognition of Farsi and Arabic handwriting is drawing increasing attention. This paper describes the result of the ICDAR 2009 competition for handwritten Farsi/Arabic character recognition. To evaluate the submitted systems, we used large datasets containing both binary and gray-scale images. Many different groups downloaded the training sets; however, finally 4 systems successfully participated in the competition. The systems were tested on two known databases and one unknown dataset. Due to the similarity between some digits and characters in Farsi and Arabic, each recognizer was tested for digit and character sets separately. For benchmarking, only the recognition rates, as the most important characteristic, are considered. Since participants used different software and even operating systems, the relative recognition speed is not compared in this competition.
  • Keywords
    handwritten character recognition; natural languages; optical character recognition; Arabic character recognition; Farsi handwriting recognition; ICDAR 2009 competition; OCR benchmarking; gray-scale image; Benchmark testing; Character recognition; Databases; Engineering drawings; Handwriting recognition; Natural languages; Optical character recognition software; Shape; Text analysis; Writing; Farsi/Arabic languages; OCR benchmarking; Performance evaluation; isolated digits and characters.; large database;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1520-5363
  • Print_ISBN
    978-1-4244-4500-4
  • Electronic_ISBN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2009.283
  • Filename
    5277795