Detection of a Large Number of Overlapping Ellipses Immersed in Noise

Authors:
Armando Manuel Fernandes
Affiliations:
CENTRIA --- Centre for Artificial Intelligence, Universidade Nova Lisboa, Quinta da Torre, Caparica, Portugal 2829-516
Venue:
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Year:
2008

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Abstract

A new algorithm able to efficiently detect a large number of overlapping ellipses with a reduced number of false positives is described. The algorithm estimates the number of candidate ellipse centers in an image with the help of a 2-dimensional accumulator and determines the five ellipse parameters with an ellipse fitting algorithm. The proposed ellipse detection algorithm uses a heuristic to select, among all image points, those with greater probabilities of belonging to an ellipse. This leads to an increase in classification efficiency, even in the presence of noise. Testing has shown that the proposed algorithm detected 97.4% of the ellipses in 100 images. Each image contained ten overlapping ellipses surrounded by noise. The ellipse parameters were determined with great accuracy.