• DocumentCode
    1472972
  • Title

    Lexicon-driven handwritten word recognition using optimal linear combinations of order statistics

  • Author

    Chen, Wen-Tsong ; Gader, Paul ; Shi, Hongchi

  • Author_Institution
    Dept. of Electr. Eng., Missouri Univ., Columbia, MO, USA
  • Volume
    21
  • Issue
    1
  • fYear
    1999
  • fDate
    1/1/1999 12:00:00 AM
  • Firstpage
    77
  • Lastpage
    82
  • Abstract
    In the standard segmentation-based approach to handwritten word recognition, individual character-class confidence scores are combined via averaging to estimate confidences in the hypothesized identities for a word. We describe a methodology for generating optimal linear combination of order statistics operators for combining character class confidence scores. Experimental results are provided on over 1000 word images
  • Keywords
    dynamic programming; handwritten character recognition; statistics; character class confidence scores; lexicon-driven handwritten word recognition; optimal linear combinations; order statistics; Character generation; Character recognition; Computer Society; Handwriting recognition; Image segmentation; Law; Legal factors; Optimization methods; Statistics; Testing;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.745738
  • Filename
    745738
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1472972