Image and Informatics Group, LBNL : Home
Image and Informatics Group, LBNL : Home

Localization of Symmetries through Iterative Voting

Int. Conf. on Pattern Reconition, 2004

    Q. Yang
    B. Parvin
    M.H. Barcellos-Hoff


    Circular symmetry is an important perceptual cue for feature-based representation, fixation, and description of large-scale dataset. A novel method based on voting along the gradient direction is introduced for inferring the center of mass for objects demonstrating circular symmetries which are not limited to convex geometries. A unique aspect of the technique is in the kernel topography, which is refined and reoriented iteratively. The technique can detect nonconvex perceptual circular symmetries, has an excellent noise immunity, and is shown to be tolerant to scale perturbation. Applications of this approach to blobs with incomplete and noisy boundaries, multimedia scenes, and scientific images are demonstrated.

    click here to see the full version of the paper in Acrobat format

    Publication number: LBNL-51202