Quality assessment of speckle patterns for DIC by consideration of both systematic errors and random errors

• A formula of root mean square error (RMSE) is derived.
• Two valid parameters are proposed to assess the quality of speckle patterns.
• An efficient algorithm is developed to estimate proposed assessment parameters.
• There is no noise-induced bias if CC criterion is used.
• A formula of interpolation bias corresponding to CC criterion is derived.

The performance of digital image correlation (DIC) is influenced by the quality of speckle patterns significantly. Thus, it is crucial to present a valid and practical method to assess the quality of speckle patterns. However, existing assessment methods either lack a solid theoretical foundation or fail to consider the errors due to interpolation. In this work, it is proposed to assess the quality of speckle patterns by estimating the root mean square error (RMSE) of DIC, which is the square root of the sum of square of systematic error and random error. Two performance evaluation parameters, respectively the maximum and the quadratic mean of RMSE, are proposed to characterize the total error. An efficient algorithm is developed to estimate these parameters, and the correctness of this algorithm is verified by numerical experiments for both 1 dimensional signal and actual speckle images. The influences of correlation criterion, shape function order, and sub-pixel registration algorithm are briefly discussed. Compared to existing methods, method presented by this paper is more valid due to the consideration of both measurement accuracy and precision.