• DocumentCode
    3329500
  • Title

    Segmentation-free printed character recognition by relaxed nearest neighbor learning of windowed operator

  • Author

    Kim, Hae Yong

  • Author_Institution
    Dept. of Electron. Eng., Sao Paulo Univ., Brazil
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    195
  • Lastpage
    204
  • Abstract
    Segmentation is considered by many researchers as the key technology for a reliable optical character recognition (OCR) system. To accomplish sound segmentation, many alternative techniques have been recently proposed. This paper presents a new technique to recognize characters without explicit segmentation. It is based on the automatic construction of a windowed operator by relaxed nearest neighbor learning. It has been implemented, tested and yielded excellent recognition accuracy and computational performance
  • Keywords
    optical character recognition; automatic windowed operator construction; computational performance; optical character recognition; recognition accuracy; relaxed nearest neighbor learning; segmentation-free printed character recognition; Character recognition; Error correction; Feedback loop; Image segmentation; Machine learning; Nearest neighbor searches; Optical character recognition software; Optical distortion; Optical feedback; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Graphics and Image Processing, 1999. Proceedings. XII Brazilian Symposium on
  • Conference_Location
    Campinas
  • Print_ISBN
    0-7695-0481-7
  • Type

    conf

  • DOI
    10.1109/SIBGRA.1999.805725
  • Filename
    805725