Sep. 2010

Article Contents

Chinese Optics> 2010> 3(4): 379-384.

YUAN Li, YE Lu, JIA Jian-lu. Ellipse detection algorithm based on Hough transform[J]. Chinese Optics, 2010, 3(4): 379-384.

Citation:

YUAN Li, YE Lu, JIA Jian-lu. Ellipse detection algorithm based on Hough transform[J].Chinese Optics, 2010, 3(4): 379-384.

YUAN Li, YE Lu, JIA Jian-lu. Ellipse detection algorithm based on Hough transform[J]. Chinese Optics, 2010, 3(4): 379-384.

Citation:

YUAN Li, YE Lu, JIA Jian-lu. Ellipse detection algorithm based on Hough transform[J].Chinese Optics, 2010, 3(4): 379-384.

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Ellipse detection algorithm based on Hough transform

1.
Changchun Institute of Optics,Fine Mechanics and Physics, Chinese Academy of Sciences,Changchun 130033,China;
2.
Graduate University of Chinese Academy of Sciences,Beijing 100039,China

Received Date:11 Mar 2010
Rev Recd Date:13 May 2010
Publish Date:25 Aug 2010

Abstract

Abstract

In order to ensure that photoelectric instruments can identify and track elliptical objects accurately, a new algorithm based on Hough transform is proposed. The new algorithm randomly samples two points, and then searches the third point using the characters of ellipse's pole and pole chord, and eliminates lots of invalid samples. In the following, it uses the three points as the centers to make three square windows, and then all the points in the windows are used to fit the ellipse. When a candidate ellipse is validated, a new method is proposed to judge if edge points are on the ellipse, and an adaptive threshold is supplied to confirm real ellipses. The experiment indicates that the algorithm's average length error is 0.5 pixel, average angle error is 0.6, and the average time needed is 79 ms. In conclusion, the algorithm has high precision and high speed, and shows a good capability of detecting ellipses.
- ellipse detecting,
- randomly sampling,
- invalid sample,
- ellipse fitting

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References (1)

References

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