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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Lamiroy, B., Guebbas, Y. (2010). Robust and Precise Circular Arc Detection. In: Ogier, JM., Liu, W., Lladós, J. (eds) Graphics Recognition. Achievements, Challenges, and Evolution. GREC 2009. Lecture Notes in Computer Science, vol 6020. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13728-0_5
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DOI: https://doi.org/10.1007/978-3-642-13728-0_5
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