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An Evaluation of Digital Image Correlation Criteria for Strain Mapping Applications
Author(s) -
Tong W.
Publication year - 2005
Publication title -
strain
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.477
H-Index - 47
eISSN - 1475-1305
pISSN - 0039-2103
DOI - 10.1111/j.1475-1305.2005.00227.x
Subject(s) - digital image correlation , digital image , computer vision , artificial intelligence , robustness (evolution) , computer science , brightness , reliability (semiconductor) , digital image processing , image (mathematics) , image processing , mathematics , optics , biochemistry , chemistry , physics , power (physics) , quantum mechanics , gene
The performance of four digital image correlation criteria widely used in strain mapping applications has been critically examined using three sets of digital images with various whole‐field deformation characteristics. The deformed images in these image sets are digitally modified to simulate the less‐than‐ideal image acquisition conditions in an actual experiment, such as variable brightness, contrast, uneven local lighting and blurring. The relative robustness, computational cost and reliability of each criterion are assessed for precision strain mapping applications. Recommendations are given for selecting a proper image correlation criterion to efficiently extract reliable deformation data from a given set of digital images.