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Performance of sub-pixel registration algorithms in digital image correlation

机译:亚像素配准算法在数字图像相关中的性能

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Developments in digital image correlation in the last two decades have made it a popular and effective tool for full-field displacement and strain measurements in experimental mechanics. In digital image correlation, the use of the sub-pixel registration algorithm is regarded as the key technique to improve accuracy. Different types of sub-pixel registration algorithms have been developed. However, little quantitative research has been carried out to compare their performances. This paper investigates three types of the most commonly used sub-pixel displacement registration algorithms in terms of the registration accuracy and the computational efficiency using computer-simulated speckle images. A detailed examination of the performances of each algorithm reveals that the iterative spatial domain cross-correlation algorithm (Newton-Raphson method) is more accurate, but much slower than other algorithms, and is recommended for use in these applications.
机译:在过去的二十年中,数字图像相关性的发展使它成为用于实验力学中全场位移和应变测量的流行且有效的工具。在数字图像相关中,使用子像素配准算法被认为是提高精度的关键技术。已经开发了不同类型的子像素配准算法。但是,很少进行定量研究来比较它们的性能。就配准精度和使用计算机模拟散斑图像的计算效率而言,本文研究了三种最常用的亚像素位移配准算法。对每种算法性能的详细检查表明,迭代空间域互相关算法(Newton-Raphson方法)更准确,但比其他算法慢得多,建议在这些应用中使用。

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