Genuine full-field deformation measurement of an object with complex shape using reliability-guided digital image correlation.

Digital image correlation (DIC) is an easy-to-implement yet powerful optical metrology for deformation measurement. The technique measures the displacement of a point of interest by matching the subsets surrounding the same point located in the reference image and the deformed image. Although the technique is simple in principle, the existing DIC technique has several deficiencies. For example, for the points located near or at the boundaries of a specified region of interest (ROI), the selected square subsets surrounding these points may contain unwanted or foreign pixels from background image or other regions. In the existing DIC method, these points are either intentionally excluded from calculation or automatically removed after calculation, and leads to the absence of deformation information for the boundary points. Besides, existing DIC technique is prone to yield erroneous measurement for specimen with geometric discontinuities. In this paper, two approaches are developed to overcome the deficiencies of existing DIC technique. First, a modified Zero-mean Normalized Sum of Squared Differences (ZNSSD) criterion is defined for the correlation analysis of subsets surrounding the boundary points. Second, considering the possible complex shape of the ROI, a scanning strategy guided by the correlation coefficients of computed points is proposed to ensure reliable computation between consecutive points. With these two measures, the deformation of all the points including those located near or at the ROI boundaries can be automatically, reliably, and accurately determined. The improved DIC technique is universally applicable to the genuine full-field deformation measurement of objects with complex or arbitrary shapes. Two typical experimental image pairs are processed to evaluate the performance of the proposed method, and the results successfully demonstrate its effectiveness and practicality.