In this paper we introduce a novel circle detection algorithm based on a weighted minimum mean square error (MSE) formulation. Traditional approaches to circle detections consist of two stages, an edge detection stage and a circle detection stage using the edge detection result. There are several problems with this approach. First, the initial edge detection stage is sensitive to noise. Second, the second stage does not use all the information available in the image and therefore incorrect decisions made by the first stage cannot be corrected in the second stage. The proposed algorithm achieves its robustness by operating in one step, using all pixels of the image (correctly weighted) and not using any thresholds. The detected circle is the solution of several weighted MSE problems. Experimental results demonstrate the performance of the algorithm in noiseless and noisy conditions.
[1]
Demetri Terzopoulos,et al.
Snakes: Active contour models
,
2004,
International Journal of Computer Vision.
[2]
Anil K. Jain,et al.
Object Matching Using Deformable Templates
,
1996,
IEEE Trans. Pattern Anal. Mach. Intell..
[3]
Aggelos K. Katsaggelos,et al.
Robust line detection using a weighted MSE estimator
,
2003,
Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).
[4]
John F. Canny,et al.
A Computational Approach to Edge Detection
,
1986,
IEEE Transactions on Pattern Analysis and Machine Intelligence.