东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2009, Vol. 30 ›› Issue (1): 121-124.DOI: -

• 论著 • 上一篇    下一篇

基于微分进化算法的轮廓匹配方法

谷雨明;刘杰;杨克实;张占一;   

  1. 东北大学机械工程与自动化学院;
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2009-01-15 发布日期:2013-06-22
  • 通讯作者: Gu, Y.-M.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(50535010)

An algorithm based on differential evolution for contour matching

Gu, Yu-Ming (1); Liu, Jie (1); Yang, Ke-Shi (1); Zhang, Zhan-Yi (1)   

  1. (1) School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2009-01-15 Published:2013-06-22
  • Contact: Gu, Y.-M.
  • About author:-
  • Supported by:
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摘要： 轮廓匹配是图像处理中一个重要匹配方法,针对现有匹配方法中匹配搜索耗时多的局限性,提出了一种改进的轮廓匹配方法.对模板图像和待匹配图像分别提取轮廓,计算轮廓上每一点的曲率,并选择满足阈值条件的轮廓点为候选点;以此点及其两侧若干点构造特征向量,依据欧氏距离构造相似性度量函数,使用具有全局最优性的微分进化算法求解,以保证获得全局最优解.对比实验表明,所提出的方法有较快的寻优速度和较高的配准率.

关键词: 轮廓, 匹配, 微分进化算法, 曲率, 欧氏距离

Abstract: Contour matching is an integral part in image processing. Analyzing the limitation of the conventional contour matching methods which take a long time to search, an improved algorithm is proposed for contour matching. In the algorithm the contours of the template image and of the image to be matched are extracted separately so as to calculate the curvature of every point on contours, and the candidate point is selected from those points on contour for satisfying the threshold. Then the eigenvectors are built at the candidate point and several points on its both sides. The comparability measurement function is built according to the Euclidean distance, and the global optimization problem is solved by differential evolution algorithm. Comparative experiment results showed that the method proposed has quick optimizing speed and high matching ability.

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