Systematic errors in digital image correlation caused by intensity interpolation

By H. Schreier, Joachim R. Braasch, Michael A. Sutton. 2000

677 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/8ea1da85a6f955f6666608efb384b70445b50e37

How researchers see this paper

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

In Computer Vision and Pattern Recognition

1. Bing Pan
2. François Hild
3. Stéphane Roux
4. J. Réthoré
5. Wei Tong
6. Zhaoyang Wang
7. Huimin Xie
8. Hugo Leclerc

In Media Technology

1. Bing Pan
2. François Hild
3. Stéphane Roux
4. Wei Tong
5. J. Réthoré
6. Zhaoyang Wang
7. Huimin Xie
8. Justin A. Blaber

Citations in the corpus

• Theoretical Analysis on the Measurement Errors of Local 2D DIC: Part I Temporal and Spatial Uncertainty Quantification of Displacement Measurements (2016, background): “Some researches have explained how intensity interpolation results in bias errors [45].”
• Digital image correlation and fracture: an advanced technique for estimating stress intensity factors of 2D and 3D cracks (2009, methodology): “Higher order interpolations (cubic, quintic spline functions [57]) are also used and they typically lead to improvements usually at the expense of longer computation”
• Comparison of Local and Global Approaches to Digital Image Correlation (2012, neutral): “However, the technique has reached centipixel standard resolutions and uncertainties [13 16], and millipixel biases or less [17,14,2,16] that are compatible with a large variety of cases encountered in solid mechanics [1 3].”
• Micro- and Nanoscale Deformation Measurement of Surface and Internal Planes via Digital Image Correlation (2007, background): “2(a), with dominant peaks at either end of the grayscale spectrum [7].”
• Improved image-based deformation measurement for geotechnical applications (2016, background): “7b presents the mean bias error, bias (Schreier et al. 2000), which is the mean discrepancy between the actual and measured displacement, for the subpixel rigid-body translation analysis.”
• Analysis of image series through global digital image correlation (2012, background): “Alternative choices can be made as in local DIC approaches [15].”
• Error Assessment in Stereo-based Deformation Measurements (2011, methodology): “Though different in form, the second term in the E(u′) expression is the “measurement bias” identified by Schreier et al in previous studies [8].”
• An Evaluation of Digital Image Correlation Criteria for Strain Mapping Applications (2005, methodology): “Surprisingly, both criteria C1 and C3 have been used widely in a significant number of strain mapping applications [1–4, 6, 13, 16, 17].”
• Performance of sub-pixel registration algorithms in digital image correlation (2006, result): “It shows high registration accuracy and good convergence character (commonly two or three iterations for each point in our calculation using computersimulated images) which is in good accordance with the results of [11].”