N-point hough transform derived by geometric duality

Authors:
Yoshihiko Mochizuki;Akihiko Torii;Atsushi Imiya
Affiliations:
School of Science and Technology, Chiba University, Chiba, Japan;Center for Machine Perception, Dept. of Cybernetics, Czech Technical University, Prague, Czech Republic;IMIT, Chiba University, Chiba, Japan
Venue:
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Year:
2006

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Abstract

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.