Quantitative Error Assessment in Pattern Matching: Effects of Intensity Pattern Noise, Interpolation, Strain and Image Contrast on Motion Measurements

By Y. Wang, Michael A. Sutton, Hugh Alan Bruck, H. Schreier. 2009

323 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/4932e0ed789be9e4c47af9ec7db3e0217751b7e7

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In Computer Vision and Pattern Recognition

1. Bing Pan
2. François Hild
3. Stéphane Roux
4. Wei Tong
5. Michel Grédiac
6. K. Li
7. Zhaoyang Wang
8. Huimin Xie

Citations in the corpus

• Equivalence of digital image correlation criteria for pattern matching. (2010, methodology): “Here, it should be noted that the DIC technique employing certain interpolation schemes, including the bicubic interpolation, will usually give rise to periodic bias error in the determined displacements [37,38].”
• Error Assessment in Stereo-based Deformation Measurements (2011, methodology): “01 pixels, is also consistent with the same previous work for the zero-motion experiment where it was shown in Ref [11] that slight shifts in the bias near an integer pixel motion will change the sign of the bias, resulting in a wider variation in bias than expected for non-integer pixel motion case”
• Fast, Robust and Accurate Digital Image Correlation Calculation Without Redundant Computations (2013, background): “This kind of systematic error distribution can be attributed to positional intensity interpolation error on sub-pixel reconstruction [32, 33].”
• Comparison of Local and Global Approaches to Digital Image Correlation (2012, methodology): “The technique has reached centipixel standard resolutions and uncertainties [13–16], and millipixel biases or less [2, 14, 16, 17] that are compatible with a large variety of cases encountered in solid mechanics [1–3].”
• Digital image correlation for surface deformation measurement: historical developments, recent advances and future goals (2018, unknown): “Wang et al theoretically deduced the governing formula of measurement bias and random errors as a function of various factors, including interpolation method, subpixel motion, image noise, image contrast, level of uniaxial normal strain, and subset size [121].”
• Theoretical Analysis on the Measurement Errors of Local 2D DIC: Part I Temporal and Spatial Uncertainty Quantification of Displacement Measurements (2016, background): “In the field of DIC, the Monte Carlo method has been adopted in some researches, e.g. References [49, 50].”
• The Grid Method for In‐plane Displacement and Strain Measurement: A Review and Analysis (2016, background): “Assessing the errors made while measuring displacement or strain components is addressed in several papers on DIC, see [149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 100, 101] for instance.”