• DocumentCode
    2183793
  • Title

    Structural Feature Extraction from Regular-Shaped Rigid Objects(1) - Based on Gradient Direction Constraint Randomized Hough Transform

  • Author

    Zhang, Lei ; Fu, Qingshan ; Zhang, Xingguo ; Hua, Guoran ; Zhu, Longbiao

  • Author_Institution
    Sch. of the Mech. Eng., Nantong Univ., Nantong, China
  • Volume
    2
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    209
  • Lastpage
    214
  • Abstract
    The structural feature extraction from regular-shaped rigid objects is studied. First, some specific measures for facilitating the conventional Randomized Hough Transform (abbr. RHT) in our application are introduced. Then, a gradient direction constraint RHT is proposed for improving the poor performance of the conventional RHT that too much false response happens in noisy real images. The basic idea of the new method is that the edge points of the true straight edges have more consistent distribution of the gradient direction than the noise has. Last, experiments including subjective observations and quantitative statistics validate that the new approach has much more robust performance than the conventional RHT.
  • Keywords
    Hough transforms; edge detection; feature extraction; edge points; noisy real images; randomized Hough transform; regular-shaped rigid objects; structural feature extraction; Randomized Hough Transform; corner detection; feature extraction; straight line extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design (ISCID), 2010 International Symposium on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4244-8094-4
  • Type

    conf

  • DOI
    10.1109/ISCID.2010.142
  • Filename
    5692771