BIROn - Birkbeck Institutional Research Online

    Application of the Fisher-Rao metric to ellipse detection

    Maybank, Stephen J. (2007) Application of the Fisher-Rao metric to ellipse detection. International Journal of Computer Vision 72 (3), pp. 287-307. ISSN 0920-5691.

    [img]
    Preview
    Text
    ellipses IJCV 3rd version.pdf - Author's Accepted Manuscript

    Download (624kB) | Preview

    Abstract

    The parameter space for the ellipses in a two dimensional image is a five dimensional manifold, where each point of the manifold corresponds to an ellipse in the image. The parameter space becomes a Riemannian manifold under a Fisher-Rao metric, which is derived from a Gaussian model for the blurring of ellipses in the image. Two points in the parameter space are close together under the Fisher-Rao metric if the corresponding ellipses are close together in the image. The Fisher-Rao metric is accurately approximated by a simpler metric under the assumption that the blurring is small compared with the sizes of the ellipses under consideration. It is shown that the parameter space for the ellipses in the image has a finite volume under the approximation to the Fisher-Rao metric. As a consequence the parameter space can be replaced, for the purpose of ellipse detection, by a finite set of points sampled from it. An efficient algorithm for sampling the parameter space is described. The algorithm uses the fact that the approximating metric is flat, and therefore locally Euclidean, on each three dimensional family of ellipses with a fixed orientation and a fixed eccentricity. Once the sample points have been obtained, ellipses are detected in a given image by checking each sample point in turn to see if the corresponding ellipse is supported by the nearby image pixel values. The resulting algorithm for ellipse detection is implemented. A multiresolution version of the algorithm is also implemented. The experimental results suggest that ellipses can be reliably detected in a given low resolution image and that the number of false detections can be reduced using the multiresolution algorithm.

    Metadata

    Item Type: Article
    Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/s11263-006-9033-z
    Keyword(s) / Subject(s): ellipse detection, Fisher-Rao metric, °at metric, geodesic, Hough transform, Kullback-Leibler distance, lattice, multiresolution, Riemannian manifold, volume of a Riemannian manifold, Voronoi's principal lattice.
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Depositing User: Professor Stephen Maybank
    Date Deposited: 30 May 2014 09:30
    Last Modified: 09 Aug 2023 12:35
    URI: https://eprints.bbk.ac.uk/id/eprint/9831

    Statistics

    Activity Overview
    6 month trend
    429Downloads
    6 month trend
    276Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item
    Edit/View Item