• DocumentCode
    2417687
  • Title

    Confidence Measure as Fuzzy Measure in Color Edge Detection

  • Author

    Soria-Frisch, Aureli ; Kassid, Abderrahim

  • Author_Institution
    Pompeu Fabra Univ., Barcelona
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1105
  • Lastpage
    1110
  • Abstract
    A framework for the detection of edges on color edges, which is based on the application of the fuzzy integral, is proposed herein. The framework makes use of the confidence measure of Meer & Georgescu (2002) in order to automate the construction of the fuzzy measure coefficients. The computation of the confidence measure is achieved by applying a competitive learning algorithm on the input images, whereby the adaptability of the mentioned algorithm is increased. This is not the only advance attained herein, since the automation of the fuzzy measure´s construction furthers the application of the fuzzy integral in computer vision. The framework has been applied in the feasibility study of a system for the reconstruction of frescos. The results in this industrial application are shown together with the performance evaluation on some benchmark images.
  • Keywords
    computer vision; edge detection; fuzzy set theory; image colour analysis; unsupervised learning; color edge detection; competitive learning algorithm; computer vision; fuzzy measure; Application software; Automation; Color; Computer vision; Construction industry; Fuzzy sets; Humans; Image edge detection; Image reconstruction; Image segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2006 IEEE International Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9488-7
  • Type

    conf

  • DOI
    10.1109/FUZZY.2006.1681848
  • Filename
    1681848