A New Conic Section Extraction Approach and Its Applications

Authors:
John Gates;Miki Haseyama;Hideo Kitajima
Affiliations:
The author is with Tokyo National College of Technology, Hachioji-shi, 193-0997 Japan. E-mail: john@tokyo-ct.ac.jp,;The authors are with the Graduate School of Engineering, Hokkaido University, Sapporo-shi, 060-8628 Japan.;The authors are with the Graduate School of Engineering, Hokkaido University, Sapporo-shi, 060-8628 Japan.
Venue:
IEICE - Transactions on Information and Systems
Year:
2005

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Abstract

This paper presents a new conic section extraction approach that can extract all conic sections (lines, circles, ellipses, parabolas and hyperbolas) simultaneously. This approach is faster than the conventional approaches with a computational complexity that is O(n), where n is the number of edge pixels, and is robust in the presence of moderate levels of noise. It has been combined with a classification tree to produce an offline character recognition system that is invariant to scale, rotation, and translation. The system was tested with synthetic images and with images scanned from real world sources with good results.