Title :
γ-ω Hough transform-elimination of quantization noise and linearization of voting curves in the ρ-&thetas; parameter space
Author :
Wada, Toshikazu ; Matsuyama, Takashi
Author_Institution :
Dept. of Inf. Technol., Okayama Univ., Japan
fDate :
30 Aug-3 Sep 1992
Abstract :
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
Keywords :
Hough transforms; edge detection; image processing; Hough transform; bias; image processing; image space; nonlinear transformation; parameter space; straight lines; uniform quantization; voting curve; Digital images; Information technology; Noise figure; Noise shaping; Pixel; Quantization; Space technology; Transforms; Voting; White noise;
Conference_Titel :
Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2920-7
DOI :
10.1109/ICPR.1992.201978