• DocumentCode
    1533493
  • Title

    A method to detect and characterize ellipses using the Hough transform

  • Author

    Bennett, Nick ; Burridge, Robert ; Saito, Naoki

  • Author_Institution
    Schlumberger-Doll Res., Ridgefield, CT, USA
  • Volume
    21
  • Issue
    7
  • fYear
    1999
  • fDate
    7/1/1999 12:00:00 AM
  • Firstpage
    652
  • Lastpage
    657
  • Abstract
    We describe a new technique for detecting and characterizing ellipsoidal shapes automatically from any type of image. This technique is a single pass algorithm which can extract any group of ellipse parameters or characteristics which can be computed from those parameters without having to detect all five parameters for each ellipsoidal shape. Moreover, the method can explicitly incorporate any a priori knowledge the user may have concerning ellipse parameters. The method is based on techniques from projective geometry and on the Hough transform. This technique can significantly reduce interpretation and computation time by automatically extracting only those features or geometric parameters of interest from images and making exact use of a priori information
  • Keywords
    Hough transforms; computational geometry; computer vision; edge detection; feature extraction; object recognition; parameter estimation; Hough transform; computer vision; edge detection; ellipses; feature extraction; parameter estimation; projective geometry; shape recognition; Computational geometry; Computational modeling; Computer vision; Data mining; Equations; Feature extraction; Image edge detection; Image sampling; Parameter estimation; Shape;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.777377
  • Filename
    777377