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计算机工程 ›› 2009, Vol. 35 ›› Issue (16): 209-210. doi: 10.3969/j.issn.1000-3428.2009.16.075

• 图形图像处理 • 上一篇    下一篇

基于自适应局部统计量的CV模型

葛 琦,张建伟,陈允杰   

  1. (南京信息工程大学数理学院,南京 210044)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-08-20 发布日期:2009-08-20

CV Model Based on Adaptive Local Statistic

GE Qi, ZHANG Jian-wei, CHEN Yun-jie   

  1. (College of Math & Physics, Nanjing University of Information Engineering, Nanjing 210044)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-08-20 Published:2009-08-20

摘要: 针对传统CV模型的分割结果易受初始曲线位置影响的问题,将传统模型与测地线模型有机结合,提出一种基于自适应局部统计量的全局优化CV模型,通过极小化能量泛函对图像进行分割,避免了收敛于局部极小的问题,采用边缘函数进行边界检测,能够较好地分割对比度较低的边界。仿真实验结果表明,与传统模型相比,该CV模型具有更高的分割精度。

关键词: CV模型, 局部非参数密度估计, 全局优化

Abstract: Aiming at the problems that cutting results are easily influenced by initial curve location in traditional CV model, it is integrated with geodesic model, and a novel global optimization CV model based on adaptive local statistic is proposed, which uses minimization energy functions to cut the images, and avoids the problem of convergence in local minima. By using edge functions, the boundary detection is conducted. It can cut the edge with low contrast. Simulation experimental results show this CV model has higher cutting accuracy compared with the existed one.

Key words: CV model, local nonparametric density estimation, global optimization

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