Application of Least Square Algorithm for Ellipses Detection

Abstract:

It is a significant process to automatically extract ellipses or elliptic image features in highly precise vision detection, especially to achieve rapid as well as accurate detection in complex environment. Fortunately, this paper provides an approach to solve the problem. We firstly detect the edge of images by using sub-pixel edge detection algorithm, and then determine the elliptical shapes, and eliminate the non-ellipses. For the complicated context and taking into account the occlusion of ellipses, we integrate the robust Hough transforms and slip window into randomized algorithm based on least square approach with the purpose of having got the veracious ellipse parameters, which proves that the approach is available for images in stability and accuracy.

• Periodical: Advanced Materials Research (Volumes 532-533)
• Pages: 1527-1531
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.532-533.1527
• Online since: June 2012
• Authors: Can Yuan, Chen Wang, Gang Liu
• Keywords: Ellipses Detection, Hough Transform (HT), Least Square Approach

References

[1] J. Qiu, Study on algorithms of evaluating the characteristic parameters of circle and ellipse, Shanxi agriculture university journal. China, vol. 29, January 2009, pp.355-357.

[2] F. Chabat, Hu Xiao-Peng, D.M. Hansell, and Yang Guang-zhong, ERS transform for the automated detection of bronchial abnormalities on CT of the lungs, IEEE Transactions on Medical Imaging. Vol. 20, September 2001, pp.942-952.

DOI: 10.1109/42.952731

[3] B. Pang, D. Zhang, and K. Wang, The bi-elliptical deformable contour and its application to automated tongue segmentation in Chinese medicine, IEEE Transactions on Medical Imaging, vol. 24(8) , August 2005, pp.946-956.

DOI: 10.1109/tmi.2005.850552

[4] D.A. Chernyak, Iris-based cyclotorsional image alignment method for wavefront registration, IEEE Transactions on Biomedical Engineering, vol. 52, December 2005, p.2032-(2040).

DOI: 10.1109/tbme.2005.857674

[5] H.F. Chen, H. Lei, Y.B. Kong, L.Y. Zhou, H.J. Feng, An improved randomized algorithm for detecting ellipses based on least square approach, Zhejiang university journal, vol. 42, August 2008, pp.1360-1364.

[6] Z.S. Lei, Y.B. Zhang, Some new algorithms for ellipse curve fitting problem, Shanghai jiaotong University journal, vol. 36, August 2002, pp.1210-1213.

[7] Chen CC. Improved moment invariants for shape discrimination, Pattern Recognition, vol. 26, May 1993, pp.683-686.

DOI: 10.1016/0031-3203(93)90121-c

[8] Fitzgibbon, M. Pilu, and R.B. Fisher. Direct least square fitting of ellipse, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, May 1999, pp.476-480.

DOI: 10.1109/34.765658