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On image gradients in digital image correlation
Summary In digital image correlation (DIC), the unknown displacement field is typically identified by minimizing the linearized form of the brightness conservation equation, while the minimization scheme also involves a linearization, yielding a two‐step linearization with four implicit assumptions....
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Published in: | International journal for numerical methods in biomedical engineering 2016-01, Vol.105 (4), p.243-260 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Summary
In digital image correlation (DIC), the unknown displacement field is typically identified by minimizing the linearized form of the brightness conservation equation, while the minimization scheme also involves a linearization, yielding a two‐step linearization with four implicit assumptions. These assumptions become apparent by minimizing the non‐linear brightness conservation equation in a consistent mathematical setting, yielding a one‐step linearization allowing a thorough study of the DIC tangent operator. Through this analysis, eight different image gradient operators are defined, and the impact of these alternative image gradients on the accuracy, efficiency, and initial guess robustness is discussed on the basis of a number of academic examples and representative test cases. The main conclusion is that for most cases, the image gradient most common in literature is recommended, except for cases with: (1) large rotations; (2) initial guess instabilities; and (3) costly iterations due to other reasons (e.g., integrated DIC), where a large deformation corrected mixed gradient is recommended instead. Copyright © 2015 John Wiley & Sons, Ltd. |
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ISSN: | 0029-5981 2040-7939 1097-0207 2040-7947 |
DOI: | 10.1002/nme.4971 |