A statistically efficient method for ellipse detection

In this paper, we introduce a statistically efficient method for detecting ellipses in an image. Given a set of digital arc segments, we introduce geometric criteria to select possible pairs of arc segments belonging to the same ellipse. The selected arc pairs are subsequently validated or rejected based on certain statistical criteria via hypothesis testing. The advantages of the technique include: 1) the proposed criteria are scale-invariant; and 2) they can automatically adapt to the noise characteristics of each image and do not need to be adjusted empirically. Performance evaluation of the technique with real images demonstrates its good performance.