Multiple ellipse fitting by center-based clustering


  • Tomislav Marošević Department of Mathematics, University of Osijek
  • Rudolf Scitovski Department of Mathematics, University of Osijek


This paper deals with the multiple ellipse fitting problem based on a given set of data points in a plane. The presumption is that all data points are derived from k ellipses that should be fitted. The problem is solved by means of center-based clustering, where cluster centers are ellipses. If the Mahalanobis distance-like function is introduced in each cluster, then the cluster center is represented by the corresponding Mahalanobis circle-center. The distance from a point $a \in \mathbb{R}^2$ to the Mahalanobis circle is based on the algebraic criterion. The well-known k-means algorithm has been adapted to search for a locally optimal partition of the Mahalanobis circle-centers. Several numerical examples are used to illustrate the proposed algorithm.






CRORR Journal Regular Issue