• DocumentCode
    457273
  • Title

    Offline Cursive Character Challenge: a New Benchmark for Machine Learning and Pattern Recognition Algorithms.

  • Author

    Camastra, Francesco ; Spinetti, Marco ; Vinciarelli, Alessandro

  • Author_Institution
    Naples Parthenope Univ., Napoli
  • Volume
    2
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    913
  • Lastpage
    916
  • Abstract
    Cursive character recognition is a challenging task due to high variability and intrinsic ambiguity of cursive letters. This paper presents C-Cube (Cursive Character Challenge), a new public-domain cursive character database. C-Cube contains 57293 cursive characters manually extracted from cursive handwritten words, including both upper and lower case versions of each letter. The database can be downoloaded from the Web and it provides predefined experimental protocols in order to compare rigorously the results obtained by different researchers
  • Keywords
    character recognition; image recognition; learning (artificial intelligence); visual databases; Cursive Character Challenge; cursive character recognition; cursive handwritten words; machine learning; pattern recognition; public-domain cursive character database; Character recognition; Classification algorithms; Databases; Feature extraction; Handwriting recognition; Machine learning; Machine learning algorithms; Pattern recognition; Protocols; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.895
  • Filename
    1699354