• DocumentCode
    2193132
  • Title

    Chapter 12: Contour Rectification and Analysis Using Circular Augmented Rotational Trajectory Algorithm

  • Author

    Apu, Russel A. ; Gavrilova, Marina L.

  • Author_Institution
    Dept. of Comput. Sci., Calgary Univ., Calgary, AB
  • fYear
    2008
  • fDate
    9-11 July 2008
  • Firstpage
    75
  • Lastpage
    81
  • Abstract
    This paper presents a novel circular augmented rotational trajectory (CART) algorithm to compute an R-space based shape descriptors which allow efficient shape matching, generalization and classification. The rotation invariant R-space representation can be used to detect invariant geometric features despite the presence of considerable noise and quantization errors. Moreover, the CART method is corner preserving and can detect the points of discontinuity in a noisy trajectory. Experimental analysis performed on a number of difficult or ambiguous object boundaries show that the CART method can correctly detect and represent the inherent shape and extract their geometric properties. The method´s universality, robustness and consistent performance on a variety of difficult shapes make it a power technique for contour representation and analysis.
  • Keywords
    computer vision; edge detection; image classification; image matching; image representation; circular augmented rotational trajectory algorithm; contour rectification; contour representation; rotation invariant R-space representation; shape matching; Algorithm design and analysis; Computer vision; Image analysis; Low pass filters; Multi-stage noise shaping; Noise shaping; Performance analysis; Robustness; Shape; Solid modeling; Computer Vision; R-Space; Shape Recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geometric Modeling and Imaging, 2008. GMAI 2008. 3rd International Conference on
  • Conference_Location
    London
  • Print_ISBN
    978-0-7695-3270-7
  • Type

    conf

  • DOI
    10.1109/GMAI.2008.10
  • Filename
    4568609