Abstract

Shape matching typically relies on the candidate shapes being normalised for scale before the matching takes place. Many methods rely on finding the boundary or normalising the area of the shape. This is problematic when the object contains holes, or two objects have different underlying shapes. The advantage of our method is that the scale can be normalised separately from the shape.

Keywords

Test Image Discrete Fourier Transform Synthetic Aperture Radar Base Image Fourier Descriptor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Alex Hughes
    • 1
  • Richard C. Wilson
    • 1
  1. 1.Department of Computer ScienceUniversity of YorkYorkUK

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