• DocumentCode
    575378
  • Title

    Robust character recognition in FA

  • Author

    Daito, A. ; Ito, Kei ; Kawagoe, Takazumi ; Murosaki, T. ; Shiose, M.

  • Author_Institution
    Machinery & Tools Dept., DENSO Corp., Chita, Japan
  • fYear
    2012
  • fDate
    20-23 Aug. 2012
  • Firstpage
    746
  • Lastpage
    751
  • Abstract
    In FA, the character with a crack or dirt cannot be recognized by pattern matching. Then, we have studied a robust character recognition with template matching and SVM (Support Vector Machine). After classifying some similar characters by template matching, one character is determined by SVM (Support Vector Machine) that is a set of related supervised learning methods. As a result, we achieved the detection margin and adjustment Time shortening.
  • Keywords
    image classification; image matching; learning (artificial intelligence); optical character recognition; support vector machines; FA; SVM; adjustment time shortening; character classification; crack; detection margin; dirt; image processing; robust character recognition; supervised learning methods; support vector machine; template matching; Cavity resonators; Character recognition; Data mining; Education; Feature extraction; Pattern matching; Support vector machines; Image Processing; SVM; Template matching; character recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE Annual Conference (SICE), 2012 Proceedings of
  • Conference_Location
    Akita
  • ISSN
    pending
  • Print_ISBN
    978-1-4673-2259-1
  • Type

    conf

  • Filename
    6318537