• DocumentCode
    2040930
  • Title

    An urn theoretical approach towards modelling of thinning algorithms

  • Author

    Ray, K. ; Ray, A.K.

  • Author_Institution
    Dept. of Electron. & Electr. Commun. Eng., Indian Inst. of Technol., Kharagpur, India
  • Volume
    2
  • fYear
    1993
  • fDate
    19-21 Oct. 1993
  • Firstpage
    914
  • Abstract
    The urn theoretic model introduced has been applied in deducing some interesting results for image processing. One of the most intuitively appealing applications of urn models is in the area of stochastic learning theory. Using this concept, the performance of a class of pattern thinning algorithms in image processing has been analysed. The performance can be visualized as the probability of a correct response in a multiple choice problem. A simple replacement model has been used for the performance analysis of some thinning algorithms.<>
  • Keywords
    image processing; learning (artificial intelligence); stochastic systems; image processing; multiple choice problem; pattern thinning; performance analysis; replacement model; stochastic learning theory; thinning algorithms; urn theoretical approach; Equations; Pixel; Skeleton; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON '93. Proceedings. Computer, Communication, Control and Power Engineering.1993 IEEE Region 10 Conference on
  • Conference_Location
    Beijing, China
  • Print_ISBN
    0-7803-1233-3
  • Type

    conf

  • DOI
    10.1109/TENCON.1993.320161
  • Filename
    320161