High-Precision 3D-DIC Measurement Method Based on Improved Forward Newton Iteration

Abstract

To solve the problems of the traditional 3D-DIC algorithm based on feature information or FFT search at the expense of accuracy in exchange for time, such as error-point extraction, mismatching of feature points, poor robustness, and accuracy loss caused by poor anti-noise performance, an improved high-precision 3D-DIC measurement method was proposed. In this method, the exact initial value is obtained by an exhaustive search. Then, the forward Newton iteration method is used for pixel classification, and the first-order nine-point interpolation is designed, which can quickly obtain the elements of Jacobian and Hazen matrix, and achieve accurate sub-pixel positioning. The experimental results show that the improved method has high accuracy, and its mean error and standard deviation stability and extreme value are better than similar algorithms. Compared with the traditional forward Newton method, the total iteration time of the improved forward Newton method is reduced in the subpixel iteration stage, and the computational efficiency is 3.8 times that of the traditional NR algorithm. The whole process of the proposed algorithm is simple and efficient, and it has application value in the precision occasions requiring high precision.