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    TAC: Thresholding active contours

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    205_2008_ICIP.pdf (165.7Kb)
    Date
    2008-10
    Author
    Dambreville, Samuel
    Yezzi, Anthony
    Lankton, Shawn
    Tannenbaum, Allen R.
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    Abstract
    In this paper, we describe a region-based active contour technique to perform image segmentation. We propose an energy functional that realizes an explicit trade-off between the (current) image segmentation obtained from a curve and the (implied) segmentation obtained from dynamically thresholding the image. In contrast with standard region-based techniques, the resulting variational approach bypasses the need to fit (a priori chosen) statistical models to the object and the background. Our technique performs segmentation based on geometric considerations of the image and contour, instead of statistical ones. The resulting flow leads to very reasonable segmentations as shown by several illustrative examples.
    URI
    http://hdl.handle.net/1853/27943
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    • Biomedical Imaging Lab (Minerva Research Group) [210]
    • Laboratory of Computational Computer Vision Publications [106]

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