Digital Image Correlation with Self-Adaptive Gaussian Windows
Publication
, Journal Article
Huang, J; Pan, X; Peng, X; Yuan, Y; Xiong, C; Fang, J; Yuan, F
Published in: Experimental Mechanics
March 1, 2013
A novel subpixel registration algorithm with Gaussian windows is put forward for accurate deformation measurement in digital image correlation technique. Based on speckle image quality and potential deformation states, this algorithm can automatically minimize the influence of subset sizes by self-adaptively tuning the Gaussian window shapes with the aid of a so-called weighted sum-of-squared difference correlation criterion. Numerical results of synthetic speckle images undergoing in-plane sinusoidal displacement fields demonstrate that the proposed algorithm can significantly improve displacement and strain measurement accuracy especially in the case with relatively large deformation. © 2012 Society for Experimental Mechanics.
Duke Scholars
Published In
Experimental Mechanics
DOI
EISSN
1741-2765
ISSN
0014-4851
Publication Date
March 1, 2013
Volume
53
Issue
3
Start / End Page
505 / 512
Related Subject Headings
- Mechanical Engineering & Transports
- 4017 Mechanical engineering
- 4005 Civil engineering
- 0915 Interdisciplinary Engineering
- 0913 Mechanical Engineering
- 0905 Civil Engineering
Citation
APA
Chicago
ICMJE
MLA
NLM
Huang, J., Pan, X., Peng, X., Yuan, Y., Xiong, C., Fang, J., & Yuan, F. (2013). Digital Image Correlation with Self-Adaptive Gaussian Windows. Experimental Mechanics, 53(3), 505–512. https://doi.org/10.1007/s11340-012-9639-8
Huang, J., X. Pan, X. Peng, Y. Yuan, C. Xiong, J. Fang, and F. Yuan. “Digital Image Correlation with Self-Adaptive Gaussian Windows.” Experimental Mechanics 53, no. 3 (March 1, 2013): 505–12. https://doi.org/10.1007/s11340-012-9639-8.
Huang J, Pan X, Peng X, Yuan Y, Xiong C, Fang J, et al. Digital Image Correlation with Self-Adaptive Gaussian Windows. Experimental Mechanics. 2013 Mar 1;53(3):505–12.
Huang, J., et al. “Digital Image Correlation with Self-Adaptive Gaussian Windows.” Experimental Mechanics, vol. 53, no. 3, Mar. 2013, pp. 505–12. Scopus, doi:10.1007/s11340-012-9639-8.
Huang J, Pan X, Peng X, Yuan Y, Xiong C, Fang J, Yuan F. Digital Image Correlation with Self-Adaptive Gaussian Windows. Experimental Mechanics. 2013 Mar 1;53(3):505–512.
Published In
Experimental Mechanics
DOI
EISSN
1741-2765
ISSN
0014-4851
Publication Date
March 1, 2013
Volume
53
Issue
3
Start / End Page
505 / 512
Related Subject Headings
- Mechanical Engineering & Transports
- 4017 Mechanical engineering
- 4005 Civil engineering
- 0915 Interdisciplinary Engineering
- 0913 Mechanical Engineering
- 0905 Civil Engineering