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基于图割与GVF Snake的凹型目标快速提取算法 被引量：2

Fast concave object extraction algorithm based on graph cuts and GVF Snake
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摘要 将图割理论与GVF Snake模型有机结合,提出了一种凹型目标的快速提取算法。首先用图割算法对初始轮廓线迭代变形,使其在快速提取非凹型段目标边界的同时将轮廓线有效地置于梯度矢量流力场的"有效逼近域"内,然后用GVF Snake算法继续对轮廓线迭代变形,提取凹型段目标边界。实验表明,该算法能快速、准确提取凹型目标。 Combining Gradient Vector Flow （GVF） Snake model with graph cuts theory, a fast concave object extraction algorithm was proposed. First the initial contour was deformed with the graph cuts algorithm, which could put the initial contour in the valid approach region of the GVF field to extract non-concave part of the object boundary. Then the active contour was input to Snake model and began its evolvement to concave part of the object boundary. Experimental results show that the algorithm can converge to concave object boundary fast and accurately.
作者 田丽丽 郭敏 徐秋平
机构地区 陕西师范大学计算机科学学院
出处 《计算机应用》 CSCD 北大核心 2008年第10期2633-2635,共3页 journal of Computer Applications
基金 陕西省自然科学基金资助项目(2005A12)
关键词 目标提取 活动轮廓模型 梯度矢量流 图割 object extraction active contour model Gradient Vector Flow （GVF） graph cuts
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献11

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二级参考文献11

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共引文献2

同被引文献18

  • 1范新南,郭建甲.一种新的自适应工程图像分割算法[J].计算机测量与控制,2006,14(3):395-397. 被引量：9
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计算机应用
2008年 第10期

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