• DocumentCode
    3110322
  • Title

    Image reconstruction for quality assessment of edge detectors

  • Author

    Govindarajan, Barghavi ; Panetta, Karen A. ; Agaian, Sos

  • Author_Institution
    Dept. of Electr. Eng., Tufts Univ., Medford, MA
  • fYear
    2008
  • fDate
    12-15 Oct. 2008
  • Firstpage
    691
  • Lastpage
    696
  • Abstract
    Extraction of the edges is a key step in image processing and there is still a continuing research effort to develop new and effective edge detection algorithms. Despite this fact, there is no single, reliable and efficient metric to evaluate the quality of an edge detector. We introduce an original method for image reconstruction that leads to edge evaluation based on image estimation. A new quantitative metric for assessment of the performance of the edge detector is also presented. The operation of the measure is established on a diverse image database using standard edge detection algorithms and the one based on partial derivatives of Boolean functions. The uses of the measure for an assortment of purposes are demonstrated and these are backed by visual assessment as well as some distance-based error functions applied on synthetic images.
  • Keywords
    Boolean functions; edge detection; image reconstruction; Boolean functions; distance based error functions; diverse image database; edge detection algorithm; edge detector; edge evaluation; image estimation; image processing; image reconstruction; quality assessment; quantitative metric; visual assessment; Boolean functions; Detectors; Image databases; Image edge detection; Image processing; Image reconstruction; Interpolation; Measurement standards; Quality assessment; Signal processing algorithms; Edge evaluation; detector parameters; image reconstruction; interpolation; quality measure; structural similarity; weighted median;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on
  • Conference_Location
    Singapore
  • ISSN
    1062-922X
  • Print_ISBN
    978-1-4244-2383-5
  • Electronic_ISBN
    1062-922X
  • Type

    conf

  • DOI
    10.1109/ICSMC.2008.4811358
  • Filename
    4811358