Digital image correlation using ring template for 3D reconstruction

Anqi Huang, Yonghong Wang, Xizuo Dan, Yue Hu, Siyuan Bao
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Abstract

Three-dimensional reconstruction is one of the most important applications of digital image correlation technology. At present, three-dimensional reconstruction of complex surface is completed by matching images caught by binocular vision measurement system. When three-dimensional objects are projected onto a two-dimensional plane image, various image factors are integrated into single gray level information. In terms of binocular vision measurement system, the images are caught by two cameras at the same time. Because of the different illumination and the stationary angle between two cameras, there might be holistic gray value differences between images caught by two cameras. These differences will affect both image matching precision and final result. In this paper, an improved binocular matching algorithm based on ring template and Newton-Raphson iteration methods is applied. To satisfy the partial convergence of Newton-Raphson iteration method, a ring template is chosen to match the integer pixel location of nodal points. After that, the integer coordinates of nodal points are already estimated which are taken as the initial value of Newton-Raphson iteration method. The morphology reconstruction of complicated surface can be implemented successfully by using algorithm mentioned in this paper. The algorithm can not only reduce the error caused by holistic gray value differences, but also improve the accuracy of reconstruction.
利用环形模板进行数字图像相关三维重建
三维重建是数字图像相关技术的重要应用之一。目前,复杂曲面的三维重建是通过双目视觉测量系统捕获的图像进行匹配来完成的。当三维物体投影到二维平面图像上时,各种图像因素被整合到单个灰度信息中。在双目视觉测量系统中,图像由两台摄像机同时捕获。由于两个摄像机之间的光照和静止角度的不同,两个摄像机拍摄的图像可能存在整体灰度值的差异。这些差异将影响图像匹配精度和最终结果。本文提出了一种改进的基于环模板和牛顿-拉夫森迭代法的双目匹配算法。为了满足Newton-Raphson迭代法的部分收敛性,选择环模板来匹配节点的整数像素位置。然后估计节点的整数坐标,作为Newton-Raphson迭代法的初始值。本文提出的算法可以成功地实现复杂表面的形态重建。该算法不仅可以减少整体灰度值差异带来的误差,而且可以提高重建的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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