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    ASIA unversity > 資訊學院 > 資訊工程學系 > 期刊論文 >  Item 310904400/18499


    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/18499


    Title: A fast and accurate snake model for object contour detection
    Authors: 莊政宏;Chuang, Cheng-Hung
    Contributors: 資訊工程學系
    Keywords: image segmentation, active contours model, deformable models, snake model, boundary detection, gradient vector flow.
    Date: 2001-05
    Issue Date: 2012-11-26 13:54:25 (UTC+8)
    Abstract: This paper presents a two-phase automatic snake algorithm for the segmentation of multiple
    objects from noisy or cluttered backgrounds. Traditional snake algorithms are often limited in their
    ability to process multiple objects and are required to have manually-drawn initial contours and fixed
    weighting parameters. Our algorithm features two phases: (1) the active-points phase and (2) the
    active-contours phase. In the first phase, grid points evenly distributed in the image are attracted and
    moved to form clusters near object boundaries. These clustered active points are then analyzed to
    obtain convex polygons as initial snake contours in the second phase, where a no-search movement
    scheme with space-varying weighting parameters is employed. Both the kinetics of active points and
    deformation of active contours accept our proposed adaptive gradient vector flow (AGVF) field as the
    contracting forces. Experiments show the stability of the AGVF field and good performance of our
    snake algorithm in segmenting multiple objects from noisy or cluttered backgrounds.
    Relation: ELECTRONICS LETTERS;1(3):296-320
    Appears in Collections:[資訊工程學系] 期刊論文

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