• DocumentCode
    650193
  • Title

    Improved Thai text detection from natural scenes

  • Author

    Woraratpanya, Kuntpong ; Boonchukusol, Pimlak ; Kuroki, Yoshimitsu ; Kato, Yu

  • Author_Institution
    Fac. of Inf. Technol., King Mongkut´s Inst. of Technol. Ladkrabang, Bangkok, Thailand
  • fYear
    2013
  • fDate
    7-8 Oct. 2013
  • Firstpage
    137
  • Lastpage
    142
  • Abstract
    Thai text detection from natural scenes is still a challenging task for language translation applications, since there are many unsolved issues. Furthermore, the existing related works cannot completely detect Thai text. The main reason is that Thai text layout has vowels and tonal marks that differ from other languages. This paper proposes an approach to detect Thai text from natural scenes. The approach consists of two main procedures. (i) Fast boundary clustering algorithm decomposes scene features into multilayers, so that it is faster and easier to analyze Thai text characters. (ii) Modified connected component analysis method is applied to such scene features in order to detect Thai text boundaries. Based on 150 test images with 4,920 characters, the experimental results demonstrate that the proposed approach achieves the high average precision and recall, 0.80 and 0.90.
  • Keywords
    character recognition; document image processing; feature extraction; language translation; natural language processing; natural scenes; pattern clustering; statistical analysis; text detection; Thai text character recognition; Thai text detection; Thai text layout; boundary clustering algorithm; language translation; modified connected component analysis; natural scene; scene feature decomposition; tonal mark; vowels; Thai text detection; fast boundary clustering; modified connected component analysis; natural scene;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Electrical Engineering (ICITEE), 2013 International Conference on
  • Conference_Location
    Yogyakarta
  • Print_ISBN
    978-1-4799-0423-5
  • Type

    conf

  • DOI
    10.1109/ICITEED.2013.6676227
  • Filename
    6676227