• DocumentCode
    249048
  • Title

    Ellipses from triangles

  • Author

    Cicconet, M. ; Gunsalus, K. ; Geiger, D. ; Werman, Michael

  • Author_Institution
    Center for Genomics & Syst. Biol., New York Univ., New York, NY, USA
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    3626
  • Lastpage
    3630
  • Abstract
    We present an ellipse finding and fitting algorithm that uses points and tangents, rather than just points, as the basic unit of information. These units are analyzed in a hierarchy: points with tangents are paired into triangles in the first layer and pairs of triangles in the second layer vote for ellipse centers. The remaining parameters are estimated via robust linear algebra: eigen-decomposition and iteratively reweighed least squares. Our method outperforms the state-of-the-art approach in synthetic images and microscopic images of cells.
  • Keywords
    computational geometry; curve fitting; eigenvalues and eigenfunctions; iterative methods; least squares approximations; object detection; parameter estimation; eigen-decomposition; ellipse detection; ellipse finding algorithm; ellipse fitting algorithm; image analysis; iteratively reweighed least squares; parameter estimation; pattern recognition; points-with-tangents; robust linear algebra; Databases; Educational institutions; Equations; Image edge detection; Pattern recognition; Robustness; Transforms; cell counting; ellipse detection; ellipse fitting; image analysis; pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025736
  • Filename
    7025736