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A neural network energy minimization approach to approximation of 2-dimensional shapes

  • Todd Law
  • Hidenori Itoh
  • Hirohisa Seki
Posters
Part of the Lecture Notes in Computer Science book series (LNCS, volume 970)

Abstract

We introduce a novel method for approximating boundaries of two-dimensional shapes using a neural network energy minimization approach. Design of the energy function allows control over the behavior of the system, which ultimately determines whether each point along the perimeter is or is not a vertex. Shapes are approximated with straight segments, circular arcs, and spiral arcs. The procedure is independent of object rotation. The method is evaluated on various shapes.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Todd Law
    • 1
  • Hidenori Itoh
    • 1
  • Hirohisa Seki
    • 1
  1. 1.Department of Artificial Intelligence and Computer ScienceNagoya Institute of TechnologyNagoyaJapan

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