基于形态学预处理的数字图像相关方法研究
Study on the method of digital image correlation based morphological pre-processing
Received:August 23, 2021  Revised:October 13, 2021
DOI:10.7520/1001-4888-21-191
中文关键词:  数字图像相关  多孔洞结构  形态学  图像预处理  图像分割
英文关键词:digital image correlation  porous structure  morphology  image pre-processing  image segmentation
基金项目:国家重点研发计划(2017YFB0102103)
Author NameAffiliation
ZAHO Jie Nanjing University of Aeronautics and Astronautics School, Nanjing 210016, Jiangsu, China 
SUN Wei* Nanjing University of Aeronautics and Astronautics School, Nanjing 210016, Jiangsu, China 
XU Zhongda Nanjing University of Aeronautics and Astronautics School, Nanjing 210016, Jiangsu, China 
LI Guojian Shanghai National Nuclear Power Plant Operation Service Technology Co., Ltd., Shanghai 200233, China 
LI Xuntao Nanjing University of Aeronautics and Astronautics School, Nanjing 210016, Jiangsu, China 
SHE Chongmin Nanjing University of Aeronautics and Astronautics School, Nanjing 210016, Jiangsu, China 
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中文摘要:
      当利用数字图像相关方法计算含孔洞结构空边的位移与应变时,往往需要消除孔洞中的背景噪声,以减小对边缘计算的影响。在边缘检测过程中,散斑边缘和孔洞边缘的灰度梯度均呈突变特征, 常会出现误将散斑边缘错判为小孔洞边缘的情况。本文提出一种基于形态学填充的图像预处理方法,该方法利用形态学操作填充散斑空隙,可避免将散斑图像边缘错误检测为小孔洞图像边缘。该方法仅对孔洞内部背景噪声等无效区域进行标记裁剪与图像分割。通过数值图像模拟与3D打印试件拉伸实验,验证了该方法对孔洞边缘测量的精度。实验结果表明,基于形态学填充的图像预处理方法能够有效消除孔内背景噪声的影响,并在相关函数计算过程中避免非散斑区域的参与。
英文摘要:
      When the displacement and strain of the edge of the porous structure are calculated using digital image correlation methods, it is often necessary to eliminate the background noise in the hole to reduce the impact on the edge calculation. However, the grayscale gradients of both the speckle edge and hole edge are abrupt changed during edge detection, so it is easy to misjudge the speckle edge as a small hole edge. In this paper, a morphological filling based image preprocessing method is proposed. This method uses morphological manipulation to fill speckle voids, which can avoid the detection of speckle image edges being misdetected as small hole image edges. The method only labels trimming and image segmentation of invalid regions such as background noise inside the hole. It also shows that eliminating the background noise improves the computational accuracy of the hole edges. The feasibility of this method is verified by numerical simulation experiments with 3D printed porous specimens. The experimental results show that the proposed image preprocessing method can effectively eliminate the influence of the background noise in the hole, avoid the calculation of the non-speckle regions, effectively improve the accuracy of the pore edge displacement and strain calculation, and realize the accurate measurement of the displacement and strain of the porous structure.
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