• DocumentCode
    296002
  • Title

    Writer verification using multiple neural networks

  • Author

    Yan, Hong ; Wu, Jing

  • Author_Institution
    Dept. of Electr. Eng., Sydney Univ., NSW, Australia
  • Volume
    1
  • fYear
    1995
  • fDate
    Nov/Dec 1995
  • Firstpage
    414
  • Abstract
    A writer identification system is described an this paper based on the use of multiple neural networks. In this system a set of Chinese characters are written by the people who are registered in the computer. One neural network is trained for all samples of each character. In the testing mode, a person is asked to write the same set of characters and the decisions of all neural network are combined to identify the person. The method has been verified to work highly reliably on real testing data and it compares favorably with the distance based method proposed by other researchers
  • Keywords
    biometrics (access control); eigenvalues and eigenfunctions; feedforward neural nets; handwriting recognition; image matching; Chinese character recognition; biometrics; eigenvalues; eigenvectors; handwriting matching; multiple neural networks; writer identification system; Computer network reliability; Databases; Eigenvalues and eigenfunctions; Humans; Law; Legal factors; Multi-layer neural network; Neural networks; Shape measurement; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1995. Proceedings., IEEE International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-2768-3
  • Type

    conf

  • DOI
    10.1109/ICNN.1995.488136
  • Filename
    488136