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Robust Circular Arc Detection

Bart Lamiroy 1 Yassine Guebbas 1
1 QGAR - Querying Graphics through Analysis and Recognition
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
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.
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https://hal.inria.fr/inria-00439459
Contributor : Bart Lamiroy <>
Submitted on : Monday, December 7, 2009 - 4:55:09 PM
Last modification on : Thursday, January 11, 2018 - 6:19:59 AM
Long-term archiving on: : Thursday, October 18, 2012 - 10:10:23 AM

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Bart Lamiroy, Yassine Guebbas. Robust Circular Arc Detection. Eighth IAPR International Workshop on Graphics Recognition - IAPR-GREC 2009, University of La Rochelle, Dec 2009, La Rochelle, France. pp.85-94. ⟨inria-00439459⟩

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