Study on subset size selection in digital image correlation for speckle patterns
Study on subset size selection in digital image correlation for speckle patterns
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DOI：
10.1364/oe.16.007037
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发表时间：
2008-05-12
期刊：
影响因子：
3.8
通讯作者：
Wang, Zhiyong
中科院分区：
文献类型：
--
作者：
Pan, Bing;Xie, Huimin;Wang, Zhiyong
数字图像相关(DIC)是一种通过将未变形图像中的参考子集与变形图像中的目标子集进行匹配来测量样品表面位移的灵活而有效的技术。对于现有的DIC技术，用户必须依靠经验和直觉来手动定义参考子集的大小，这被发现对测量位移的准确性至关重要。本文研究了DIC技术中的子集大小选择问题。基于差值平方和(SSD)相关准则和图像噪声灰度梯度远低于散斑图像灰度梯度的假设，推导了DIC位移测量精度的理论模型。理论模型表明，基于图像噪声的方差和子集强度梯度平方和(SSSIG)可以准确预测DIC的位移测量精度。该模型进一步为DIC分析选择合适的子集大小提供了一个简单的标准。数值实验验证了所提概念的正确性，计算结果与理论预测吻合较好。C 2008美国光学学会。
Digital Image Correlation (DIC) has been established as a flexible and effective technique to measure the displacements on specimen surface by matching the reference subsets in the undeformed image with the target subsets in the deformed image. With the existing DIC techniques, the user must rely on experience and intuition to manually define the size of the reference subset, which is found to be critical to the accuracy of measured displacements. In this paper, the problem of subset size selection in the DIC technique is investigated. Based on the Sum of Squared Differences (SSD) correlation criterion as well as the assumption that the gray intensity gradients of image noise are much lower than that of speckle image, a theoretical model of the displacement measurement accuracy of DIC is derived. The theoretical model indicates that the displacement measurement accuracy of DIC can be accurately predicted based on the variance of image noise and Sum of Square of Subset Intensity Gradients (SSSIG). The model further leads to a simple criterion for choosing a proper subset size for the DIC analysis. Numerical experiments have been performed to validate the proposed concepts, and the calculated results show good agreements with the theoretical predictions. c 2008 Optical Society of America.