Digital image correlation based on variable circle template in dual camera matching

Abstract

In the measurement of the 3-D shape of a large curved object using traditional 3-D-digital image correlation (DIC), the left and right camera images are relatively rotated or deformed too much, which will cause the matching to fail. We propose a 3D-DIC matching method. Compared with traditional methods having fixed-size templates, this method is robust to relative rotation and deformation between dual cameras and is suitable for 3D-DIC measurement of nonplanar objects. In the proposed method, we use polar coordinates to define the matching template as a variable circle, which is convenient for interpolation calculation and changing the template size. The zero-mean normalized cross-correlation method is used to determine the position of an entire pixel on the distorted image. This step can provide an initial value close to the true value for subsequent iterations of the inverse compositional Gauss–Newton algorithm. The performance of the proposed method is verified by experiments. Compared with the traditional matching method, the proposed method is suitable for matching large curved surfaces between 3D-DIC dual cameras and extends the application of DIC technology.