Curves Detection Using Delaunay Triangulation Based on Perceptual Grouping Factors

  • Takagi Takamitsu
    Department of Information Science, Faculty of Engineering, Gifu University
  • Saitoh Fumihiko
    Department of Information Science, Faculty of Engineering, Gifu University

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  • 群化要因に基づくドロネー分割を用いた視覚的連続曲線の認識
  • グンカ ヨウイン ニ モトズク ドロネー ブンカツ オ モチイタ シカクテキ レンゾク キョクセン ノ ニンシキ

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Abstract

In this paper, we propose a method to detect perceptual continuous curves in a binary image including discontinuous curves and noises based on perceptual grouping factors. Firstly, making a Delaunay diagram from a binary image, adjacency relation is obtained. Secondly, the method selects a Delaunay edge as the starting line and connects a certain number of points. When the points have maximum evaluation value based on perceptual grouping factors, they construct an appropriate partial curve. Evaluation value of an appropriate partial curve is added to Delaunay edges selected by it. Finally, Delaunay edges that have high evaluation value are extracted. Experimental results show that proposed method has yielded results that are similar to visual curves and better than conventional methods.

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