• DocumentCode
    2459261
  • Title

    Enhancing intellectual power of recognition systems based on new pattern recognition theory

  • Author

    Fedotov, Nikolay G. ; Shulga, Lyudmila A.

  • Author_Institution
    Penza State Univ., Russia
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    192
  • Lastpage
    197
  • Abstract
    Application of stochastic geometry methods to pattern recognition is analyzed. The discourse is based on trace transformations of original images introduced by (Fedotov, 1990) into images on the Mobius band. Based on the new geometric transformation, a new approach towards the construction of features, independent of image motions or their linear transformations, is put forward. A prominent characteristics of the group of features under consideration is representing each of them as a consecutive composition of three functionals. Such a structure of features helps automatically generate a greater number of new constructive signs of recognition. Such a powerful shift of stress from the decision procedures onto features´ mass application, accounts for speaking about a new interpretation of images, and enhancing intellectual power of recognition systems.
  • Keywords
    computational geometry; pattern recognition; Mobius band; decision procedures; image interpretation; image trace transformations; pattern recognition theory; stochastic geometry; Artificial intelligence; Character recognition; Geometry; Humans; Image recognition; Pattern analysis; Pattern recognition; Psychology; Stochastic processes; Stress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence Systems, 2002. (ICAIS 2002). 2002 IEEE International Conference on
  • Print_ISBN
    0-7695-1733-1
  • Type

    conf

  • DOI
    10.1109/ICAIS.2002.1048086
  • Filename
    1048086