Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Apr 8;23(8):3834.
doi: 10.3390/s23083834.

A Comparative Study of Structural Deformation Test Based on Edge Detection and Digital Image Correlation

Ruixiang Tang  1 , Wenbing Chen  1 , Yousong Wu  1 , Hongbin Xiong  1 , Banfu Yan  1   2
Affiliations

A Comparative Study of Structural Deformation Test Based on Edge Detection and Digital Image Correlation

Ruixiang Tang et al. Sensors (Basel). .

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.

Keywords: Canny; Zernike moments; deformation test; digital image correlation; digital image processing.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The structure of this article.
Figure 2
Figure 2
Schematic Diagram of Edge Detection Test Principle.
Figure 3
Figure 3
The step model of Zernike moment.
Figure 4
Figure 4
Schematic diagram of DIC test principle.
Figure 5
Figure 5
Target map for simulation experiment; (a) Original picture of DIC simulation experiment; (b) Translate down 1 pixel; (c) Original pictures of DIP simulation experiment; (d) Pan down 1 pixel.
Figure 6
Figure 6
Performance evaluation of three algorithms (where N is before filtering and F is after filtering): (a) error variance; and (b) root mean square error.
Figure 7
Figure 7
Performance evaluation of simulation experiment algorithm: (a) displacement—error mean diagram; and (b) displacement-error mean square diagram.
Figure 8
Figure 8
Algorithm speed comparison: (a) DIC algorithm; (b) DIP before CUDA acceleration; and (c) DIP after CUDA acceleration.
Figure 9
Figure 9
Step displacement measuring system.
Figure 10
Figure 10
Performance evaluation of laboratory experimental algorithms: (a) mean error; (b) error variance; and (c) variation of error percentage with distance.
Figure 11
Figure 11
Site conditions of real bridge experiment: (a) site layout of the bridge test: (b) site target layout.
Figure 12
Figure 12
Displacement time history curve: (a) before EMD filtering; and (b) after EMD filtering.
Figure 13
Figure 13
Performance evaluation of real bridge experiment algorithm: (a) mean error; (b) variance; and (c) mean square error.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Silva-Campillo A., Pérez-Arribas F., Suárez-Bermejo J.C. Health-Monitoring Systems for Marine Structures: A Review. Sensors. 2023;23:2099. doi: 10.3390/s23042099. - DOI - PMC - PubMed
    1. Komarizadehasl S., Mobaraki B., Ma H., Lozano-Galant J.-A., Turmo J. Development of a Low-Cost System for the Accurate Measurement of Structural Vibrations. Sensors. 2021;21:6191. doi: 10.3390/s21186191. - DOI - PMC - PubMed
    1. Gian Michele C., Matteo M., Nicola S., Volkan O., Paolo Martino C., Rui P. Numerical Investigations on the Collapse of the Morandi Bridge. Springer Tracts Transp. Traffic. 2021;17:3–18.
    1. Schwarzbach P., Michler A., Tauscher P., Michler O. An Empirical Study on V2X Enhanced Low-Cost GNSS Cooperative Positioning in Urban Environments. Sensors. 2019;19:5201. doi: 10.3390/s19235201. - DOI - PMC - PubMed
    1. Ye X.W., Dong C.Z. Overview of structural displacement monitoring based on computer vision. J. China Highw. 2019;32:21–39.