Mean intensity gradient: An effective global parameter for quality assessment of the speckle patterns used in digital image correlation

Abstract

Digital image correlation (DIC) is an image-based optical metrology for full-field deformation measurement. In DIC technique, the test object surface must be covered with a random speckle pattern, which deforms together with the object surface as a carrier of deformation information. In practice, the speckle patterns may show distinctly different intensity distribution characteristics and have an important influence on DIC measurements. How to assess the overall quality of different speckle patterns with a simple yet effective parameter is an interesting but confusing problem, and is also helpful to the optimal use of the technique. In this paper, a novel, simple, easy-to-calculate yet effective global parameter, called mean intensity gradient, is proposed for quality assessment of the speckle patterns used in DIC. To verify the correctness and effectiveness of the new concept, five different speckle patterns are numerically translated, and the displacements measured with DIC are compared with the exact ones. The errors are evaluated in terms of mean bias error and standard deviation error. It is shown that both mean bias error and standard deviation of the measured displacement are closely related to the mean intensity gradient of the speckle pattern used, and a so-called good speckle pattern should be of large mean intensity gradient.