Bornert, Michel and Brémand, Fabrice and Doumalin, Pascal and Dupré, Jean-Christophe and Fazzini, Marina and Grédia, Michel and Hild, François and Mistou, Sébastien and Molimard, Jérôme and Orteu, Jean-José and Robert, Laurent and Surrel, Yves and Vacher, Pierre and Wattrisse, Bertrand Assessment of digital image correlation measurement errors: methodology and results. (2009) Experimental Mechanics, 49 (3). 353-370. ISSN 0014-4851
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(Document in English)
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Official URL: http://dx.doi.org/10.1007/s11340-008-9204-7
Abstract
Optical full-field measurement methods such as Digital Image Correlation (DIC) are increasingly used in the field of experimental mechanics, but they still suffer from a lack of information about their metrological performances. To assess the performance of DIC techniques and give some practical rules for users, a collaborative work has been carried out by the Workgroup “Metrology” of the French CNRS research network 2519 “MCIMS (Mesures de Champs et Identification en Mécanique des Solides / Full-field measurement and identification in solid mechanics, http://www.ifma.fr/lami/gdr2519)”. A methodology is proposed to assess the metrological performances of the image processing algorithms that constitute their main component, the knowledge of which being required for a global assessment of the whole measurement system. The study is based on displacement error assessment from synthetic speckle images. Series of synthetic reference and deformed images with random patterns have been generated, assuming a sinusoidal displacement field with various frequencies and amplitudes. Displacements are evaluated by several DIC packages based on various formulations and used in the French community. Evaluated displacements are compared with the exact imposed values and errors are statistically analyzed. Results show general trends rather independent of the implementations but strongly correlated with the assumptions of the underlying algorithms. Various error regimes are identified, for which the dependence of the uncertainty with the parameters of the algorithms, such as subset size, gray level interpolation or shape functions, is discussed.
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