Robust ellipse detection via arc segmentation and classification

In this paper, we propose a novel ellipse detection algorithm for synthetic and real images. Existing ellipse detection methods are too slow when used with limited hardware resources. The proposed method demonstrates the capability of detecting ellipses with an excellent accuracy at an acceptable speed level in three public datasets. The excellent performance is attributed to the novel combination of classification of arcs into different quadrants of a candidate ellipse, edge curvature and convexity-concavity analysis, and an elliptic geometry constraint.