• DocumentCode
    2161721
  • Title

    A Fast and Accurate Algorithm for Chessboard Corner Detection

  • Author

    Zhu Weixing ; Ma Changhua ; Xia Libing ; Li Xincheng

  • Author_Institution
    Modern Agric. Equip. & Technol. Key Lab. of Jiangsu Province, Jiangsu Univ., Zhenjiang, China
  • fYear
    2009
  • fDate
    17-19 Oct. 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The authors point out the limitations of SUSAN corner detector in detecting chessboard corner, then describe an improved SUSAN(smallest univalue segment assimilating nucleus) detector algorithm for detecting chessboard corner on the basis of symmetrical geometry structure of USAN (univalue segment assimilating nucleus) area. And the algorithm has been applied to the chessboard images on real photos. The improved algorithm can quickly detect corner from real photos shot from every angle. The theory of detecting corner at sub-pixel level is orthogonal vector theory, that is, vector from the corner to its adjacent area pixel point should be vertical to gray grads of the adjacent area pixel point. In order to get the coordinate of corner at sub-pixel level, we establish the neighboring area equation and solve it via iterative method, and propose to check its validity according to cross ratio invariability in perspective projection.
  • Keywords
    image resolution; image segmentation; iterative methods; SUSAN corner detector; USAN area; chessboard corner detection; chessboard images; cross ratio invariability; iterative method; orthogonal vector theory; smallest univalue segment assimilating nucleus; subpixel level; symmetrical geometry; univalue segment assimilating nucleus; Agriculture; Calibration; Cameras; Detectors; Equations; Image edge detection; Image segmentation; Orbital robotics; Robot kinematics; Robotics and automation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4244-4129-7
  • Electronic_ISBN
    978-1-4244-4131-0
  • Type

    conf

  • DOI
    10.1109/CISP.2009.5304332
  • Filename
    5304332