γ-ω Hough transform-elimination of quantization noise and linearization of voting curves in the ρ-&thetas; parameter space.

It is known that the ρ-θ parameter space has inherent bias, and it has been treated as the appearance of the white noise in the image space. In this paper, the authors first show that the bias is caused by the uniform quantization of the parameter space. To eliminate the bias, a new parameter γ representing a nonuniform quantization along the ρ-axis is introduced and the γ-θ parameter space is constructed. In this space, the uniform quantization does not introduce any bias. Then, by a nonlinear transformation of θ, the γ-ω parameter space is derived, in which a voting curve becomes a pair of straight lines preserving the unbiasedness

Digital Object Identifier: 10.1109/ICPR.1992.201978
Published with permission from the copyright holder. This is the institute's copy, as published in Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 11th IAPR International Conference on, 30 Aug.-3 Sept. 1992, Pages 272-275.
Publisher URL:http://dx.doi.org/10.1109/ICPR.1992.201978
Copyright © 1992 IEEE. All rights reserved.