School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China.
Sensors (Basel). 2023 Mar 21;23(6):3317. doi: 10.3390/s23063317.
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.
为了解决传统基于特征信息或 FFT 搜索的 3D-DIC 算法在牺牲精度以换取时间的问题,例如误点提取、特征点不匹配、鲁棒性差以及抗噪声性能差导致的精度损失,提出了一种改进的高精度 3D-DIC 测量方法。在该方法中,通过穷举搜索获得精确的初始值。然后,使用前向牛顿迭代法进行像素分类,并设计了一阶九点插值,可以快速获得雅可比和海森矩阵的元素,实现精确的亚像素定位。实验结果表明,改进后的方法具有较高的精度,其均值误差和标准差稳定性以及极值均优于类似算法。与传统的前向牛顿法相比,改进的前向牛顿法在亚像素迭代阶段的总迭代时间减少,计算效率是传统 NR 算法的 3.8 倍。该算法的整个过程简单高效,在需要高精度的精密场合具有应用价值。