• DocumentCode
    153369
  • Title

    Performance Improvement in Local Feature Based Camera-Captured Character Recognition

  • Author

    Matsuda, Tadamitsu ; Iwamura, Mikio ; Kise, Kenji

  • Author_Institution
    Dept. of CSIS, Osaka Prefecture Univ., Sakai, Japan
  • fYear
    2014
  • fDate
    7-10 April 2014
  • Firstpage
    196
  • Lastpage
    201
  • Abstract
    Concerning camera-captured Japanese character recognition, we have proposed a method to recognize characters, both simple and complex, that may not be linearly aligned and may be printed with a complex background. Recognition is performed based on local features and their arrangement. The arrangement is validated with an algorithm called local RANSAC. However, at least four corresponding local features are required. To relax that condition, we propose a new recognition method making it possible to recognize a character region with at least three corresponding local features. This method enables recall and precision to be improved with the simpler characters using more corresponding local features and computation times to be reduced by 7%.
  • Keywords
    character recognition; object recognition; random processes; camera-captured Japanese character recognition; local RANSAC; local feature; Character recognition; Databases; Feature extraction; Image recognition; Robustness; Text recognition; Vectors; RANSAC; affine transformation matrix; local feature; reference point; scene character recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis Systems (DAS), 2014 11th IAPR International Workshop on
  • Conference_Location
    Tours
  • Print_ISBN
    978-1-4799-3243-6
  • Type

    conf

  • DOI
    10.1109/DAS.2014.78
  • Filename
    6830997