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Image and Informatics Group, LBNL : Home

Perceptual Organization of Radial Symmetries

IEEE Conference on Computer Vision and Pattern Reconition, 2004

    Q. Yang
    B. Parvin

    ABSTRACT

    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 perceptual 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.
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    Publication number: LBNL-51202