Using Image Gradients to Improve Robustness of Digital Image Correlation to Non-uniform Illumination: Effects of Weighting and Normalization Choices

Handle URI:
http://hdl.handle.net/10754/566187
Title:
Using Image Gradients to Improve Robustness of Digital Image Correlation to Non-uniform Illumination: Effects of Weighting and Normalization Choices
Authors:
Xu, Jiangping; Moussawi, Ali ( 0000-0002-5978-7990 ) ; Gras, Renaud; Lubineau, Gilles ( 0000-0002-7370-6093 )
Abstract:
Changes in the light condition affect the solution of intensity-based digital image correlation algorithms. One natural way to decrease the influence of illumination is to consider the gradients of the image rather than the image itself when building the objective function. In this work, a weighted normalized gradient-based algorithm, is proposed. This algorithm optimizes the sum-of-squared difference between the weighted normalized gradients of the reference and deformed images. Due to the lower sensitivity of the gradient to the illumination variation, this algorithm is more robust and accurate than the intensity-based algorithm in case of illumination variations. Yet, it comes with a higher sensitivity to noise that can be mitigated by designing the relevant weighting and normalization of the image gradient. Numerical results demonstrate that the proposed algorithm gives better results in case of linear/non-linear space-based and non-linear gray value-based illumination variation. The proposed algorithm still performs better than the intensity-based algorithm in case of illumination variations and noisy data provided the images are pre-smoothed with a Gaussian low-pass filter in numerical and experimental examples.
KAUST Department:
Physical Sciences and Engineering (PSE) Division
Publisher:
Springer Nature
Journal:
Experimental Mechanics
Issue Date:
5-Mar-2015
DOI:
10.1007/s11340-015-9996-1
Type:
Article
ISSN:
00144851
Sponsors:
Funding for this research was provided by KAUST baseline funding. The authors are grateful to KAUST for its financial support. We are also grateful to Justin Blaber of the Georgia Institute of Technology for providing open source codes [28].
Appears in Collections:
Articles; Physical Sciences and Engineering (PSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorXu, Jiangpingen
dc.contributor.authorMoussawi, Alien
dc.contributor.authorGras, Renauden
dc.contributor.authorLubineau, Gillesen
dc.date.accessioned2015-08-12T09:31:40Zen
dc.date.available2015-08-12T09:31:40Zen
dc.date.issued2015-03-05en
dc.identifier.issn00144851en
dc.identifier.doi10.1007/s11340-015-9996-1en
dc.identifier.urihttp://hdl.handle.net/10754/566187en
dc.description.abstractChanges in the light condition affect the solution of intensity-based digital image correlation algorithms. One natural way to decrease the influence of illumination is to consider the gradients of the image rather than the image itself when building the objective function. In this work, a weighted normalized gradient-based algorithm, is proposed. This algorithm optimizes the sum-of-squared difference between the weighted normalized gradients of the reference and deformed images. Due to the lower sensitivity of the gradient to the illumination variation, this algorithm is more robust and accurate than the intensity-based algorithm in case of illumination variations. Yet, it comes with a higher sensitivity to noise that can be mitigated by designing the relevant weighting and normalization of the image gradient. Numerical results demonstrate that the proposed algorithm gives better results in case of linear/non-linear space-based and non-linear gray value-based illumination variation. The proposed algorithm still performs better than the intensity-based algorithm in case of illumination variations and noisy data provided the images are pre-smoothed with a Gaussian low-pass filter in numerical and experimental examples.en
dc.description.sponsorshipFunding for this research was provided by KAUST baseline funding. The authors are grateful to KAUST for its financial support. We are also grateful to Justin Blaber of the Georgia Institute of Technology for providing open source codes [28].en
dc.publisherSpringer Natureen
dc.subjectDigital image correlationen
dc.subjectIllumination variationen
dc.subjectImage matchingen
dc.subjectInverse compositional image alignmenten
dc.subjectNormalized gradienten
dc.titleUsing Image Gradients to Improve Robustness of Digital Image Correlation to Non-uniform Illumination: Effects of Weighting and Normalization Choicesen
dc.typeArticleen
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.identifier.journalExperimental Mechanicsen
kaust.authorXu, Jiangpingen
kaust.authorMoussawi, Alien
kaust.authorGras, Renauden
kaust.authorLubineau, Gillesen
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.