• DocumentCode
    1637673
  • Title

    Information Retrieval Model for Online Handwritten Script Identification

  • Author

    Tan, Guo Xian ; Viard-gaudin, Christian ; Kot, Alex C.

  • Author_Institution
    Nanyang Technol. Univ., Singapore, Singapore
  • fYear
    2009
  • Firstpage
    336
  • Lastpage
    340
  • Abstract
    Script identification has always been a topic of much research interest in the field of document analysis. The accurate determination of the identity of the script is paramount to many post-processing steps such as document sorting, translation and in determining the choice of linguistic resources to use for OCR or handwriting recognition. However, few works exist with regards to the identification of online handwritten scripts, partly due to the large variations and challenges innate in handwritten scripts. This paper proposes a novel approach for online handwritten script identification based on the information retrieval model. We attempt to identify among three script families; Arabic, Roman and Tamil scripts, which attained an average accuracy of 93.3% from our results. This signifies promising potential in utilizing information retrieval models for script identification.
  • Keywords
    document image processing; handwriting recognition; handwritten character recognition; image retrieval; optical character recognition; OCR; document analysis; document sorting; document translation; handwriting recognition; information retrieval model; linguistic resource; online handwritten script identification; Computer science; Delay; Handwriting recognition; Information retrieval; Ink; Robustness; Support vector machine classification; Support vector machines; Text analysis; Voting; Information retrieval; Online handwriting; Script identification;
  • 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.2009.162
  • Filename
    5277680