A novel ellipse detection method for real-time applications

Limin Zhang; Feng Zhu; Yingming Hao; Wang Pan

doi:10.1117/12.2505381

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12 December 2018 A novel ellipse detection method for real-time applications

Limin Zhang, Feng Zhu, Yingming Hao, Wang Pan

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Proceedings Volume 10846, Optical Sensing and Imaging Technologies and Applications; 1084626 (2018) https://doi.org/10.1117/12.2505381
Event: International Symposium on Optoelectronic Technology and Application 2018, 2018, Beijing, China

Abstract

The detection of ellipses in digital image data is an important task in vision-based systems, since elliptical shapes are very common in nature and in man-made objects. Ellipse detection in real images is technically a very challenging problem in detection effectiveness and execution time. We propose an improved ellipse detection method for real-time performance on real world images. We extract arcs from the edge mask and classify them in four classes according to edge direction and convexity. By developing arc selection strategy, we select a combination of arcs possibly belonging to the same ellipse, and then estimate its parameters via the least squares fitting technique. Candidate ellipses are validated according to the fitness of the estimation with the actual edge pixels. Our method has been tested on three real images datasets and compared with two state-of-the-art methods. Our method performs superior than the compared methods. The results also show that the proposed method is suitable for real-time applications.

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Limin Zhang, Feng Zhu, Yingming Hao, and Wang Pan "A novel ellipse detection method for real-time applications", Proc. SPIE 10846, Optical Sensing and Imaging Technologies and Applications, 1084626 (12 December 2018); https://doi.org/10.1117/12.2505381

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