Abstract:
Digital image-correlation (DIC) algorithms rely heavily on the accuracy of the initial values provided by whole-pixel search algorithms for structural displacement monitoring. When the measured displacement is too large or exceeds the search domain, the calculation time and memory consumption of the DIC algorithm will increase greatly, and even fail to obtain the correct result. The paper introduced two edge-detection algorithms, Canny and Zernike moments in digital image-processing (DIP) technology, to perform geometric fitting and sub-pixel positioning on the specific pattern target pasted on the measurement position, and to obtain the structural displacement according to the change of the target position before and after deformation. This paper compared the difference between edge detection and DIC in accuracy and calculation speed through numerical simulation, laboratory, and field tests. The study demonstrated that the structural displacement test based on edge detection is slightly inferior to the DIC algorithm in terms of accuracy and stability. As the search domain of the DIC algorithm becomes larger, its calculation speed decreases sharply, and is obviously slower than the Canny and Zernike moment algorithms.
摘要:
数字图像相关(DIC)算法在很大程度上依赖于全像素搜索算法提供的初始值的准确性,以进行结构位移监测。当测量的位移过大或超过搜索域时,DIC算法的计算时间和内存消耗将大大增加,甚至无法获得正确的结果。本文介绍了两种边缘检测算法,Canny和Zernike在数字图像处理(DIP)技术中的应用,对粘贴在测量位置上的特定图案目标进行几何拟合和亚像素定位,根据目标位置变形前后的变化得到结构位移。本文通过数值模拟比较了边缘检测与DIC在精度和计算速度上的差异,实验室,和现场测试。研究表明,基于边缘检测的结构位移测试在精度和稳定性方面略逊于DIC算法。随着DIC算法的搜索域变大,它的计算速度急剧下降,显然比Canny和Zernike矩算法慢。