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Robust and Precise Circular Arc Detection

  • Bart Lamiroy
  • Yassine Guebbas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6020)

Abstract

In this paper we present a method to robustly detect circular arcs in a line drawing image. The method is fast, robust and very reliable, and is capable of assessing the quality of its detection. It is based on Random Sample Consensus minimization, and uses techniques that are inspired from object tracking in image sequences. It is based on simple initial guesses, either based on connected line segments, or on elementary mainstream arc detection algorithms. Our method consists of gradually deforming these circular arc candidates as to precisely fit onto the image strokes, or to reject them if the fitting is not possible, this virtually eliminates spurious detections on the one hand, and avoiding non-detections on the other hand.

Keywords

Cover Percentage Black Pixel Circle Radius Symbol Recognition Random Sample Consensus 
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 2010

Authors and Affiliations

  • Bart Lamiroy
    • 1
  • Yassine Guebbas
    • 1
  1. 1.Nancy Université – INPL – LORIA, Équipe Qgar – Bât. BVandoeuvre-lès-Nancy CedexFrance

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