Quality assessment of laser speckle patterns for digital image correlation by a Multi-Factor Fusion Index

Abstract

Digital image correlation based on laser speckle has its unique advantages in ultra-high temperature deformation measurement. The traditional quality assessment criteria of artificial speckle which consider only the contrast of the speckle pattern or the morphology of the speckle particles are not suitable for laser speckle. Here, a new index, called Multi-Factor Fusion Index (MFFI), which takes the inhomogeneity of gray distribution, the mean square deviation of gray and the standard deviation of speckle particles size into consideration, is proposed to evaluate the quality of laser speckle patterns. Multi-Factor Fusion Index was compared with three commonly used criteria, the mean intensity gradient, the mean intensity of the second derivative, and the pattern quality metric combining the sum of square of subset intensity gradients (SSSIG) and the secondary auto-correlation peak height. The results showed that the proposed index had better capability of assessing the quality of laser speckle patterns. And the influence by external factors such as apertures, laser powers and temperatures and material factors such as roughness and light reflectance were analyzed by MFFI. Experiments on artificial speckle showed that MFFI was also suitable for artificial speckle patterns in most cases.