北京航空航天大学学报 ›› 2008, Vol. 34 ›› Issue (12): 1441-1444.

• 论文 • 上一篇    下一篇

规则图像特征的标准互相关相似函数

孙明磊1, 张 融1, 朱小峰2, 宗光华1   

  1. 1. 北京航空航天大学 机械工程及自动化学院, 北京 100191;
    2. 北京市劳动保护科学研究所, 北京 100054
  • 收稿日期:2007-12-23 出版日期:2008-12-31 发布日期:2010-09-16
  • 作者简介:孙明磊(1974-),男,湖北襄樊人,博士后,sunminglei@gmail.com.
  • 基金资助:

    中国博士后科学基金资助项目(20070420287);国家863计划资助项目(2004AA404260)

Normalized cross correlation computation for geometry image features

Sun Minglei1, Zhang Rong1, Zhu Xiaofeng2, Zong Guanghua1   

  1. 1. School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
    2. Beijing Municipal Institute of Labour Protection, Beijing 100054, China
  • Received:2007-12-23 Online:2008-12-31 Published:2010-09-16

摘要: 利用标准互相关算子对机器视觉领域常用的十字图像特征进行匹配运算,发现相似函数在峰值区域的分布特征为4个互相对称的双曲面.受此启发,对规则几何图像特征(如矩型、圆型等)的标准互相关相似函数展开了研究.以图像特征概率分布的形式给出了NCCO算子在二值图像匹配下的相似函数计算式.推导并证明了矩型、圆型等典型图像特征相似函数在峰值点区域具有确定的数学模型.基于上述数学模型,在微装配显微视觉系统上进行了实验验证,对模板优化、图像特征的尺寸等优化方法进行了探讨.上述结论对图像定位、图像标定、图像跟踪等技术研究具有实用价值.

Abstract: Normalized cross correlation operator (NCCO) was used for pattern matching to localize popular cross-shaped features in microscopic vision. Distribution feature of similarity function around peak zone was found to be four symmetry hyperboloid planes. Inspired by this, some research work on pattern matching of geometry image features (such as rectangular, circular, etc.) was presented. A probability distribution based formula computing NCCO with two binary images was proposed. Mathematic models of some typical geometry image features- (rectangular, circular, cross-type, box-type) similar functions around peak point were derived from and proved. Based on these models, some experiments about template image optimum and feature size optimum were conducted on a microscopic vision workcell. Conclusions above are practically useful to image positioning, image calibration and image tracking techniques.

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