## 1 Introduction  
Digital image correlation (DIC) is one of a number of optical full-field technologies used to measure the shape and deformation characteristics of a wide range of materials. The theory and principles of DIC can be read in various publications [1; 2]. Due to the multi-faceted nature of DIC systems, there are numerous variables that can introduce errors into the measurement chain, which can be grouped into two categories: measurement quality (imaging hardware, lighting, etc.) and the correlation principle (algorithm, processing variables, speckle pattern, etc.) [3]. All DIC systems require a _system calibration_ to be performed before a measurement can commence and numerous articles have been published outlining the best practice [4; 5; 6; 7; 8; 9; 10]. A system calibration enables image points on the camera's CCD to be transformed to the corresponding 3D coordinates of that point and determines imaging parameters such as lens distortion, camera positions, and orientations [11]. The quality of the calibration process is usually reported by means of a calibration score, which is typically based on the difference between the reconstructed point and the extracted point [6]. This score, however, does not indicate the uncertainty in a subsequent strain measurement as it does not take into account correlation errors. Numerous studies have attempted to investigate each error source in isolation; a study by [PERSON] used a combination of experimental and numerical techniques to decouple sources of error, including the environment, lighting, speckle pattern, subset size, grid pitch, translations, and rotations of the sample [3]. Testing was based on the rigid-body motion of an undeformed sample, where measured strain was equated to measurement error as, theoretically, it should have been zero. Strain errors of up to \(5\times 10^{-3}\) were reported for each source. The method used by [PERSON] has the benefit of being simple; however, it does not take into account any errors associated with the distortion of subsets during large deformations. The focus of this study, however, is to develop an applied experimental method that will enable a DIC practitioner to perform a traceable full-field measurement calibration to evaluate a particular equipment setup in a real-world environment related to their specific application. Even though a number of 2D and 3D DIC systems are commercially available and there has been considerable growth in the use of DIC, the procedures for calibrating DIC systems for full-field strain measurement have lagged behind [12]. Recent initiatives have led to the publication of A Good Practices Guide for Digital Image Correlation [10], which considers the influence of variance errors and bias errors on measurement uncertainty. The guide recommends computing spatial and temporal standard deviations of the quantity of interest from images of a static, undeformed test piece to quantify variance errors. It also suggests a number of options for investigating bias errors by analysing the rigid body motion of the test piece, but it acknowledges that these approaches are not sufficient to fully evaluate all bias errors. This is because the quantification of bias errors requires the true value of a quantity of interest to be known [10]. A _measurement calibration_ is used to understand the performance of a measurement system through the comparison of measurements made against a reliable, calibrated source [12]. Calibrations can be used to explore the influence of variables in the measurement process on the accuracy of a measurement. Understanding these influences improves confidence in the reliability of both singular and comparative measurements, as well as supporting the refinement of experimental design. The challenges faced in the creation of experimental calibration methodologies for optical techniques include controlling the uniformity and intensity of strain fields [13], establishing a traceable calibration measurement, and calibrating measurements that are both full-field and dynamic [14].