Mean intensity gradient: An effective global parameter for quality assessment of the speckle patterns used in digital image correlation
By Bing Pan, Zi-Xing Lu, Huimin Xie. 2010
549 citations recorded by the source corpus.
Subfields: Computational Mechanics, Computer Vision and Pattern Recognition, Media Technology
View Paper: https://www.semanticscholar.org/paper/4eb83921d63d010f0213bc251ccd22243a41259e
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In Computational Mechanics
In Computer Vision and Pattern Recognition
In Media Technology
Citations in the corpus
- Application of Digital Image Correlation (DIC) in Dynamic Notched Semi-Circular Bend (NSCB) Tests (2014, methodology): “The span of the supporting pins S is 38 mm. Optimal speckle patterns have an average speckle size in the range of 3 to 7 pixels as suggested by Sutton [37, 38], and they could also be optimized using the mean intensity gradient as suggested by Pan [39].”
- Digital image correlation for surface deformation measurement: historical developments, recent advances and future goals (2018, methodology): “To quantitatively evaluate the quality of speckle patterns, a global parameter called the mean intensity gradient (MIG) was proposed by Pan et al in 2000 [139], which was extended from the local parameter SSSIG previously defined for quality assessment of a local speckle pattern within individual su”
- Dense dispersed shear bands in gradient-structured Ni (2020, background): “6, meaning a high correlation coefficient for strain calculation (Pan et al., 2010).”
- High-temperature digital image correlation method for full-field deformation measurement at 1200 °C (2010, methodology): “To ensure reliable and accurate measurements using DIC, natural or artificial speckle patterns with random variations of grayscale intensity must be available on the specimen surface as a carrier of deformation information [23, 24].”
- Recent Progress in Digital Image Correlation (2011, unknown): “[9-12].”
- Plastic Strain Mapping with Sub-micron Resolution Using Digital Image Correlation (2013, unknown): “Assessmentof theDICsystematicerror associated to the pattern quality as described in [30] was not carried out.”
- 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].”
- Fast, Robust and Accurate Digital Image Correlation Calculation Without Redundant Computations (2013, methodology): “A series of translated speckle images for each speckle pattern were generated by applying the appropriate shift in Fourier domain according to shift theorem [32].”