• DocumentCode
    1636426
  • Title

    Indian Multi-Script Full Pin-code String Recognition for Postal Automation

  • Author

    Pal, U. ; Roy, R.K. ; Roy, K. ; Kimura, F.

  • Author_Institution
    Comput. Vision & Pattern Recognition Unit, Indian Stat. Inst., Kolkata, India
  • fYear
    2009
  • Firstpage
    456
  • Lastpage
    460
  • Abstract
    Under three-language formula, the destination address block of postal document of an Indian state is generally written in three languages: English, Hindi and the State official language. Because of inter-mixing of these scripts in postal address writings, it is very difficult to identify the script by which a pin-code is written. Also, because of the writing style of different individuals some of the digits in a pin-code string may touch with its neighboring digits. Accurate segmentation of such touching components into individual digits is a difficult task. To avoid such difficulties, in this paper we proposed a tri-lingual (English, Hindi and Bangla) 6-digit full pin-code string recognition. We obtained 99.01% reliability from our proposed system when error and rejection rates are 0.83% and 15.27%, respectively.
  • Keywords
    document handling; natural language processing; pattern recognition; postal services; Indian string recognition; destination address block; multiscript full pin-code string recognition; postal address writings; postal automation; postal document; scripts intermixing; state official language; Automation; Computer vision; Databases; Natural languages; Optical character recognition software; Pattern analysis; Pattern recognition; Statistics; Text analysis; Writing; Handwriting recognition; Indian Postal Automation; Multi-lingual OCR; Postal Automation;
  • 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.2009.171
  • Filename
    5277632