Digital Image Correlation with Self-Adaptive Gaussian Windows |
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Authors: | J. Huang X. Pan X. Peng Y. Yuan C. Xiong J. Fang F. Yuan |
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Affiliation: | 1. College of Engineering, Peking University, Beijing, 100871, Peoples Republic of China 2. Department of Biomedical Engineering, Duke University, Durham, NC, 27708, USA
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Abstract: | 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. |
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