Quality assessment of speckle patterns for digital image correlation

By David Lecompte, A. Smits, S. Bossuyt, H. Sol, J. Vantomme, Danny van Hemelrijck, A. Habraken. 2006

565 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/e651bd2cb3a5770377a629d8bfb183058ceb4a70

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Bing Pan
2. Zhaoyang Wang
3. Huimin Xie
4. Michael A. Sutton
5. T. Siebert
6. F. Matta
7. Pedro P. Camanho
8. R. Ghorbani

In Computer Vision and Pattern Recognition

1. Bing Pan
2. Zhaoyang Wang
3. Huimin Xie
4. P. Lava
5. Benoît Blaysat
6. Michael A. Sutton
7. Giacomo Lionello
8. T. Siebert

In Media Technology

1. Bing Pan
2. Zhaoyang Wang
3. Huimin Xie
4. P. Lava
5. Michael A. Sutton
6. F. Matta
7. Benoît Blaysat
8. R. Ghorbani

Citations in the corpus

• A practical approach to optimizing the preparation of speckle patterns for digital-image correlation (2014, methodology): “Each image of speckle pattern was analyzed with the mathematical morphology technique [17, 18].”
• Full-Field Deformation Measurement and Crack Mapping on Confined Masonry Walls Using Digital Image Correlation (2014, methodology): “To maximize accuracy, the subset size used in the correlation analysis must be tailored to provide a distinctive intensity pattern to distinguish one subset from the others [6].”
• Recent Progress in Digital Image Correlation (2011, background): “[ 3 ], a more straightforward, easy-to-calculate global parameter to assess the quality of the entire speckle pattern would be more preferable to the users of DIC.”
• A Good Practices Guide for Digital Image Correlation (2018, background): “12More advanced “optimized” pattern designs are outside the scope of the current edition of this guide, but information can be found in [2, 5, 11].”
• Measurement of resistance curves in the longitudinal failure of composites using digital image correlation (2010, background): “Typically, a larger facet size will improve the precision of the measurements but also will degrade the spatial resolution [22].”
• Equivalence of digital image correlation criteria for pattern matching. (2010, methodology): “It should be noted first that the test specimen surface must be covered with a random speckle pattern in the DIC technique, which serves as a carrier of deformation information [19 – 21].”