Digital Image Correlation with Self-Adaptive Gaussian Windows

被引:55
作者
Huang, J. [1 ,2 ]
Pan, X. [1 ]
Peng, X. [1 ]
Yuan, Y. [1 ]
Xiong, C. [1 ]
Fang, J. [1 ]
Yuan, F. [2 ]
机构
[1] Peking Univ, Coll Engn, Beijing 100871, Peoples R China
[2] Duke Univ, Dept Biomed Engn, Durham, NC 27708 USA
基金
中国国家自然科学基金;
关键词
Deformation measurement; Speckle pattern; Digital image correlation; Subpixel registration algorithm; Optimal subset size; SYSTEMATIC-ERRORS; SUBSET SIZE; DISPLACEMENT;
D O I
10.1007/s11340-012-9639-8
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A novel subpixel registration algorithm with Gaussian windows is put forward for accurate deformation measurement in digital image correlation technique. Based on speckle image quality and potential deformation states, this algorithm can automatically minimize the influence of subset sizes by self-adaptively tuning the Gaussian window shapes with the aid of a so-called weighted sum-of-squared difference correlation criterion. Numerical results of synthetic speckle images undergoing in-plane sinusoidal displacement fields demonstrate that the proposed algorithm can significantly improve displacement and strain measurement accuracy especially in the case with relatively large deformation.
引用
收藏
页码:505 / 512
页数:8
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