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应用科学学报 ›› 2005, Vol. 23 ›› Issue (1): 31-36.

• 论文 • 上一篇    下一篇

一种稳健的目标提取与跟踪算法

杨晓辉, 李中科, 吴乐南   

  1. 东南大学无线电工程系, 江苏南京 210096
  • 收稿日期:2003-10-31 修回日期:2003-12-31 出版日期:2005-01-31 发布日期:2005-01-31
  • 作者简介:杨晓辉(1968-),女,辽宁沈阳人,副教授,博士生,E-mail:xhyang@seu.edu.cn;吴乐南(1952-),男,安徽枞阳人,教授,博导.

A Robust Scheme for Contour Extracting and Tracking

YANG Xiao-hui, LI Zhong-ke, WU Le-nan   

  1. Department of Radio Engineering, Southeast University, Nanjing 210096, China
  • Received:2003-10-31 Revised:2003-12-31 Online:2005-01-31 Published:2005-01-31

PDF

92

被引次数

13

摘要： 融合了GVF-Snakes算法与基于细粒度的遗传算法,提出了一种稳健的目标轮廓提取与跟踪算法.该算法通过使用边界约束替代能量计算改进了GVF-Snakes算法,降低了算法计算复杂度,提高了它的搜索速度;另外,通过引用细粒度遗传算法来筛选控制点序列,提高了算法对极端凹陷边缘和噪声干扰轮廓的提取能力.通过合成和自然图像的目标轮廓提取和跟踪实验,证明了本文提出的算法具有鲁棒性和精确性.

关键词: 活动轮廓, 遗传算法, 细粒度模型, GVF-Snakes

Abstract: A new scheme is proposed to extract and track the object contour automatically in this paper, it combines the active contour based on the gradient vector flow(GVF-Snakes) and the genetic algorithm (GA) based on the fine-grained model.On the one hand, the GVF-Snakes is improved by using the edge criterion instead of the complex energy computation to reduce its complexity and speed up its search.On the other hand, the selection of the array of the reference points by the GA enhances the extracting performance of the extreme concave contours and noise-disturbing contours.Experiment on the synthetic and natural images demonstrate its robustness and accuracy.

Key words: GVF-Snakes, genetic algorithm, active contour, fine-grained model

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