Capturing outlines of planar images by cubic spline using stochastic evolution

  • M. Sarfraz*
  • , M. T. Parvez
  • , S. M.A.J. Rizvi
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

This paper is concerned with a new technique of curve fitting. The technique has various phases including extracting outlines of images, detecting corner points from the detected outline, addition of extra knot points if needed. The last phase makes a significant contribution by making the technique automated. It uses the idea of Stochastic Evolution to optimize the shape parameters in the description of the generalized cubic spline. It ultimately produces optimal results for the approximate vectorization of the digital contour obtained from the planar images.

Original languageEnglish
Title of host publicationComputer Graphics, Imaging and Visualisation
Subtitle of host publicationNew Advances, CGIV 2007
Pages255-260
Number of pages6
DOIs
StatePublished - 2007

Publication series

NameComputer Graphics, Imaging and Visualisation: New Advances, CGIV 2007

Keywords

  • Cubic spline
  • Curve fitting
  • Knot insertion
  • Planar image
  • Soft computing

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

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