A fast and robust ellipse detector based on top-down least-square fitting

Yongtao Wang, Zheqi He, Xicheng Liu, Zhi Tang and Luyuan Li

Abstract

Ellipse detection is a very important problem in the field of pattern recognition and computer vision. The existing algorithms often use a bottom-up strategy to combine edge points or elliptical arcs into ellipses, hence limit their robustness. In this paper, we propose a fast and robust ellipse detection algorithm which can accurately detect ellipses in the images. The main idea of the proposed algorithm is to exploit a novel top-down fitting strategy to combine edge points into ellipses and use integral chain to speed up the fitting process. Experimental results have demonstrated that our ellipse detection algorithm achieves a better performance than the state-of-the-art methods on the common evaluation measures of F1 score and average execution time.

Session

Poster 2

Files

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DOI

10.5244/C.29.156
https://dx.doi.org/10.5244/C.29.156

Citation

Yongtao Wang, Zheqi He, Xicheng Liu, Zhi Tang and Luyuan Li. A fast and robust ellipse detector based on top-down least-square fitting. In Xianghua Xie, Mark W. Jones, and Gary K. L. Tam, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 156.1-156.12. BMVA Press, September 2015.

Bibtex

@inproceedings{BMVC2015_156,
	title={A fast and robust ellipse detector based on top-down least-square fitting},
	author={Yongtao Wang and Zheqi He and Xicheng Liu and Zhi Tang and Luyuan Li},
	year={2015},
	month={September},
	pages={156.1-156.12},
	articleno={156},
	numpages={12},
	booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
	publisher={BMVA Press},
	editor={Xianghua Xie, Mark W. Jones, and Gary K. L. Tam},
	doi={10.5244/C.29.156},
	isbn={1-901725-53-7},
	url={https://dx.doi.org/10.5244/C.29.156}
}