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Digital image correlation and tracking is an optical method that employs tracking and image registration techniques for accurate 2D and 3D measurements of changes in images. This method is often used to measure full-field displacement and strains , and it is widely applied in many areas of science and engineering.
The common idea of image registration and digital image correlation is to find the transformation between a fixed image and a moving one for a given metric using an optimization scheme. While there are many methods to achieve such a goal, Yadics focuses on registering images with the same modality.
The full-field monitoring capabilities of an image correlation technique allow for the measurement of strain magnitude and location on the surface of a specimen during a displacement-causing event, [10] such as PCBA during a thermal profile. These "strain maps" allow for the comparison of strain levels over full areas of interest.
Strain can also be measured using digital image correlation (DIC). With this technique one or two cameras are used in conjunction with a DIC software to track features on the surface of components to detect small motion. The full strain map of the tested sample can be calculated, providing similar display as a finite-element analysis.
Figure 1: Measured strain distribution of a tensile test (shape memory alloy) during loading and unloading shows moving Lüders bands. The measurement was performed with a LIMESS Digital image correlation system. As internal stresses tend to be highest at the shoulders of tensile test specimens, band formation is favored in those areas.
Tensile testing, also known as tension testing, [1] is a fundamental materials science and engineering test in which a sample is subjected to a controlled tension until failure. Properties that are directly measured via a tensile test are ultimate tensile strength , breaking strength , maximum elongation and reduction in area. [ 2 ]
Phase correlation is an approach to estimate the relative translative offset between two similar images (digital image correlation) or other data sets. It is commonly used in image registration and relies on a frequency-domain representation of the data, usually calculated by fast Fourier transforms .
The structural similarity index measure (SSIM) is a method for predicting the perceived quality of digital television and cinematic pictures, as well as other kinds of digital images and videos. It is also used for measuring the similarity between two images.