Back to Search
Start Over
Pixel-level robust digital image correlation
- Source :
- OPTICS EXPRESS
- Publication Year :
- 2013
-
Abstract
- Digital Image Correlation (DIC) is a well-established non-contact optical metrology method. It employs digital image analysis to extract the full-field displacements and strains that occur in objects subjected to external stresses. Despite recent DIC progress, many problematic areas which greatly affect accuracy and that can seldomly be avoided, received very little attention. Problems posed by the presence of sharp displacement discontinuities, reflections, object borders or edges can be linked to the analysed object’s properties and deformation. Other problematic areas, such as image noise, localized reflections or shadows are related more to the image acquisition process. This paper proposes a new subset-based pixel-level robust DIC method for in-plane displacement measurement which addresses all of these problems in a straightforward and unified approach, significantly improving DIC measurement accuracy compared to classic approaches. The proposed approach minimizes a robust energy functional which adaptively weighs pixel differences in the motion estimation process. The aim is to limit the negative influence of pixels that present erroneous or inconsistent motions by enforcing local motion consistency. The proposed method is compared to the classic Newton-Raphson DIC method in terms of displacement accuracy in three experiments. The first experiment is numerical and presents three combined problems: sharp displacement discontinuities, missing image information and image noise. The second experiment is a real experiment in which a plastic specimen is developing a lateral crack due to the application of uniaxial stress. The region around the crack presents both reflections that saturate the image intensity levels leading to missing image information, as well as sharp motion discontinuities due to the plastic film rupturing. The third experiment compares the proposed and classic DIC approaches with generic computer vision optical flow methods using images from the popular Middlebury optical flow evaluation dataset. Results in all experiments clearly show the proposed method’s improved measurement accuracy with respect to the classic approach considering the challenging conditions. Furthermore, in image areas where the classic approach completely fails to recover motion due to severe image de-correlation, the proposed method provides reliable results.
- Subjects :
- Digital image correlation
Technology and Engineering
Computer science
ILLUMINATION
Optical flow
SEGMENTATION
Image processing
Sensitivity and Specificity
Pattern Recognition, Automated
Optics
Motion estimation
Digital image processing
Image Interpretation, Computer-Assisted
Image noise
Computer Graphics
Segmentation
OPTIMIZATION
Image restoration
DISPLACEMENT
MOTION ESTIMATION
Pixel
business.industry
OPTICAL-FLOW
Reproducibility of Results
Signal Processing, Computer-Assisted
Velocimetry
Image Enhancement
FIELDS
Atomic and Molecular Physics, and Optics
Subtraction Technique
business
Algorithms
DEFORMATION MEASUREMENT
Subjects
Details
- Language :
- English
- ISSN :
- 10944087
- Database :
- OpenAIRE
- Journal :
- OPTICS EXPRESS
- Accession number :
- edsair.doi.dedup.....f8877496ce9be5770dc2c04d8117a430