• DocumentCode
    3206845
  • Title

    A geometric approach to machine-printed character recognition

  • Author

    Wang, Li ; Pavlidis, Theo

  • Author_Institution
    Dept. of Comput. Sci., State Univ. of New York, Stony Brook, NY, USA
  • fYear
    1992
  • fDate
    15-18 Jun 1992
  • Firstpage
    665
  • Lastpage
    668
  • Abstract
    An approach to feature extraction that eliminates binarization by extracting features directly from gray scale images is presented. It not only allows the processing of poor quality input (e.g., low contrast, dirty images), but also offers the possibility of significantly lower resolution for digitization
  • Keywords
    character recognition; feature extraction; geometry; image recognition; digitization; dirty images; feature extraction; geometry; gray scale images; image resolution; low contrast; machine-printed character recognition; poor quality input processing; Character recognition; Computer science; Feature extraction; Graphics; Image resolution; Image sensors; Optical character recognition software; Printers; Shape; Surface topography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on
  • Conference_Location
    Champaign, IL
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-2855-3
  • Type

    conf

  • DOI
    10.1109/CVPR.1992.223206
  • Filename
    223206
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3206845