• DocumentCode
    3173659
  • Title

    Discriminant performance of the algebraic features of handwritten character images

  • Author

    Liu, Ke ; Huang, Yea-Shuan ; Suen, Ching Y. ; Yang, Jing-Yu ; Liu, Lei- Jian ; Liu, Ying- Jiang

  • Author_Institution
    Centre for Pattern Recognition & Machine Intelligence, Concordia Univ., Montreal, Que., Canada
  • Volume
    2
  • fYear
    1994
  • fDate
    9-13 Oct 1994
  • Firstpage
    426
  • Abstract
    One of the most important topics in handwritten character recognition is the extraction of features from character images. In this paper, an algebraic feature extraction technique is applied to recognize handwritten characters. The discriminant performance of the algebraic features extracted from both handprinted characters and totally unconstrained handwritten numerals is studied. Experimental results are provided
  • Keywords
    character recognition; algebraic feature extraction; handwritten character recognition; optimal discriminant criterion; totally unconstrained handwritten numerals; Character recognition; Computer science; Feature extraction; Handwriting recognition; Image analysis; Image recognition; Machine intelligence; Scattering; Shape; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1994. Vol. 2 - Conference B: Computer Vision & Image Processing., Proceedings of the 12th IAPR International. Conference on
  • Conference_Location
    Jerusalem
  • Print_ISBN
    0-8186-6270-0
  • Type

    conf

  • DOI
    10.1109/ICPR.1994.576972
  • Filename
    576972