• DocumentCode
    1567251
  • Title

    Detection of dominant points based on noise suppression and error minimisation

  • Author

    Shearer, Mathew ; Zou, Ju Jia

  • Author_Institution
    Sch. of Eng. & Ind. Design, Western Sydney Univ., NSW, Australia
  • Volume
    1
  • fYear
    2005
  • Firstpage
    772
  • Abstract
    Approximation of contours has been shown to be reliant upon accurate determination of the region of support. In this paper, it is proposed that an adaptive approach will provide improved results and better shape representation. Local optimisation of chords along with desensitising the arc-chord measure to small perturbations is used. Experiment results show that the proposed method is superior to existing methods.
  • Keywords
    minimisation; pattern recognition; arc-chord measure; contour approximation; dominant point detection; error minimisation; local optimisation; noise suppression; shape representation; Approximation algorithms; Australia; Design engineering; Feature extraction; Humans; Joining processes; Noise measurement; Noise robustness; Pattern recognition; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Applications, 2005. ICITA 2005. Third International Conference on
  • Print_ISBN
    0-7695-2316-1
  • Type

    conf

  • DOI
    10.1109/ICITA.2005.115
  • Filename
    1488905