N-Point Hough Transform Derived by Geometric Duality

  • Yoshihiko Mochizuki
  • Akihiko Torii
  • Atsushi Imiya
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4319)


We propose an extension of the three-point Randomized Hough transform. Our new Hough transform, which permits a continuous voting space without any cell-tessellation, uses both one-to-one mapping from an image plane to the parameter space and from the parameter space to the image plane. These transforms define a parameter from samples and a line from a parameter, respectively. Furthermore, we describe the classical Hough transform, the randomized Hough transform, the three-point randomized Hough transform and our new Hough transform in a generalized framework using geometric duality.


Parameter Space Sample Point Original Image Image Plane Great Circle 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yoshihiko Mochizuki
    • 1
  • Akihiko Torii
    • 2
  • Atsushi Imiya
    • 3
  1. 1.School of Science and TechnologyChiba UniversityChibaJapan
  2. 2.Center for Machine Perception, Dept. of CyberneticsCzech Technical UniversityPragueCzech Republic
  3. 3.IMITChiba UniversityChibaJapan

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