Accurate displacement measurement via a self-adaptive digital image correlation method based on a weighted ZNSSD criterion

Digital image correlation (DIC) technique has been increasingly employed to implement surface deformation measurements in many engineering fields. Practically, it has been demonstrated that the choice of subset sizes exerts a strong influence on measurement results of DIC, especially when there exis...

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Veröffentlicht in:Optics and lasers in engineering Jg. 52; S. 75 - 85
Hauptverfasser: Yuan, Yuan, Huang, Jianyong, Peng, Xiaoling, Xiong, Chunyang, Fang, Jing, Yuan, Fan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.01.2014
Schlagworte:
Algorithms
Correlation analysis
Criteria
Deformation
Deformation measurement
Digital
Displacement measurement
Gaussian
Gaussian window
Self-adaptive algorithm
Subpixel registration
Subset size
Deformation measurement
Gaussian window
Self-adaptive algorithm
Subpixel registration
Subset size
ISSN:0143-8166, 1873-0302
Online-Zugang:Volltext
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Zusammenfassung:Digital image correlation (DIC) technique has been increasingly employed to implement surface deformation measurements in many engineering fields. Practically, it has been demonstrated that the choice of subset sizes exerts a strong influence on measurement results of DIC, especially when there exists locally larger deformation over the subsets involved. This paper proposes a novel subpixel registration algorithm with Gaussian windows to implicitly optimize the subset sizes by adjusting the shape of Gaussian windows in a self-adaptive fashion with the aid of a so-called weighted zero-normalized sum-of-squared difference correlation criterion. The feasibility and effectiveness of the self-adaptive algorithm are carefully verified through a set of well-designed synthetic speckle images, which indicates that the presented algorithm is able to greatly enhance the accuracy and precision of displacement measurements as compared with the traditional subpixel registration methods.
Bibliographie:ObjectType-Article-2
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ISSN:0143-8166
1873-0302
DOI:10.1016/j.optlaseng.2013.07.016