• DocumentCode
    3061732
  • 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
  • fYear
    1992
  • fDate
    30 Aug-3 Sep 1992
  • Firstpage
    272
  • Lastpage
    275
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • 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
  • Type

    conf

  • DOI
    10.1109/ICPR.1992.201978
  • Filename
    201978