Digital image correlation (DIC) and digital volume correlation (DVC) are powerful means of resolving local kinematic descriptions of material deformation fields across a variety of material and testing platforms. Their spatial resolution, sensitivity, and accuracy depend in large part on the quality of the intrinsic material speckle pattern. Traditional evaluation of speckle pattern quality, or subset intensity distribution, relies on a set of well-characterized experimental measurements including rigid-body translation and rotation. In order to provide a significantly faster quantitative evaluation process on whether a particular speckle pattern is suitable for DIC or DVC purposes, we present a simple, intuitive DIC and DVC speckle pattern graphical user interface (GUI) tool programmed in matlab. This tool assesses the DIC and DVC robustness of user-supplied speckle patterns via a two-step procedure: The first step involves warping the specific image according to a set of analytically prescribed deformation functions. The second step involves correlating the analytically warped and reference image pairs to recover the prescribed displacement field and its quantitative comparison to the prescribed warping function. Since the accuracy and precision of the recovered solution depend on the characteristics of the intensity distributions encoded in the image, this approach allows for a simple, yet effective, quantification procedure of the correlation suitability in the supplied image speckle pattern. In short, this procedure allows for fast and quantitative evaluation of the quality and suitability of a given speckle pattern to be used in DIC and DVC applications without the need of performing time-consuming experimental measurements. As such, we hope that this free tool will benefit anyone interested in performing DIC- or DVC-based kinematic measurements.

References

References
1.
Hild
,
F.
, and
Roux
,
S.
,
2012
,
Digital Image Correlation
,
Wiley-VCH
,
Weinheim, Germany
.
2.
Gates
,
M.
,
Lambros
,
J.
, and
Heath
,
M. T.
,
2011
, “
Towards High Performance Digital Volume Correlation
,”
Exp. Mech.
,
51
(
4
), pp.
491
507
.10.1007/s11340-010-9445-0
3.
Sutton
,
M. A.
,
Orteu
,
J. J.
, and
Schreier
,
H.
,
2009
,
Image Correlation for Shape, Motion and Deformation Measurements: Basic Concepts, Theory and Applications
,
Springer
,
New York
.
4.
Du
,
Y.
,
Diaz
,
F. A.
,
Burguete
,
R. L.
, and
Patterson
,
E. A.
,
2011
, “
Evaluation Using Digital Image Correlation of Stress Intensity Factors in an Aerospace Panel
,”
Exp. Mech.
,
51
(
1
), pp.
45
57
.10.1007/s11340-010-9335-5
5.
Blaber
,
J.
,
Adair
,
B. S.
, and
Antoniou
,
A.
,
2015
, “
A Methodology for High Resolution Digital Image Correlation in High Temperature Experiments
,”
Rev. Sci. Instrum.
,
86
(
3
), p.
035111
.10.1063/1.4915345
6.
Grassi
,
L.
,
Väänänen
,
S. P.
,
Yavari
,
S. A.
,
Jurvelin
,
J. S.
,
Weinans
,
H.
,
Ristinmaa
,
M.
,
Zadpoor
,
A. A.
, and
Isaksson
,
H.
,
2014
, “
Full-Field Strain Measurement During Mechanical Testing of the Human Femur at Physiologically Relevant Strain Rates
,”
ASME J. Biomech. Eng.
,
136
(
11
), p.
111010
.10.1115/1.4028415
7.
Toyjanova
,
J.
,
Flores-Cortez
,
E.
,
Reichner
,
J. S.
, and
Franck
,
C.
,
2015
, “
Matrix Confinement Plays a Pivotal Role in Regulating Neutrophil-Generated Tractions, Speed and Integrin Utilization
,”
J. Biol. Chem.
,
290
(
6
), pp.
3752
3763
.10.1074/jbc.M114.619643
8.
Ambu
,
R.
,
Aymerich
,
F.
, and
Bertolino
,
F.
,
2005
, “
Investigation of the Effect of Damage on the Strength of Notched Composite Laminates by Digital Image Correlation
,”
J. Strain Anal. Eng. Des.
,
40
(
5
), pp.
451
461
.10.1243/030932405X16106
9.
Bormann
,
T.
,
Schulz
,
G.
,
Deyhle
,
H.
,
Beckmann
,
F.
,
de Wild
,
M.
,
Küffer
,
J.
,
Münch
,
C.
,
Hoffmann
,
W.
, and
Müller
,
B.
,
2014
, “
Combining Micro Computed Tomography and Three-Dimensional Registration to Evaluate Local Strains in Shape Memory Scaffolds
,”
Acta Biomater.
,
10
(
2
), pp.
1024
1034
.10.1016/j.actbio.2013.11.007
10.
Kim
,
K.
, and
Daly
,
S.
,
2011
, “
Martensite Strain Memory in the Shape Memory Alloy Nickel-Titanium Under Mechanical Cycling
,”
Exp. Mech.
,
51
(
4
), pp.
641
652
.10.1007/s11340-010-9435-2
11.
Coudrillier
,
B.
,
Pijanka
,
J.
,
Jefferys
,
J.
,
Sorensen
,
T.
,
Quigley
,
H. A.
,
Boote
,
C.
, and
Nguyen
,
T. D.
,
2015
, “
Collagen Structure and Mechanical Properties of the Human Sclera: Analysis for the Effects of Age
,”
ASME J. Biomech. Eng.
,
137
(
4
), p.
041006
.10.1115/1.4029430
12.
Abanto-Bueno
,
J.
, and
Lambros
,
J.
,
2002
, “
Investigation of Crack Growth in Functionally Graded Materials Using Digital Image Correlation
,”
Eng. Fract. Mech.
,
69
(
14–16
), pp.
1695
1711
.10.1016/S0013-7944(02)00058-9
13.
Bay
,
B. K.
,
Smith
,
T. S.
,
Fyhrie
,
D. P.
, and
Saad
,
M.
,
1999
, “
Digital Volume Correlation: Three-Dimensional Strain Mapping Using X-Ray Tomography
,”
Exp. Mech.
,
39
(
3
), pp.
217
226
.10.1007/BF02323555
14.
Kammers
,
A. D.
, and
Daly
,
S.
,
2013
, “
Digital Image Correlation Under Scanning Electron Microscopy: Methodology and Validation
,”
Exp. Mech.
,
53
(
9
), pp.
1743
1761
.10.1007/s11340-013-9782-x
15.
Bar-Kochba
,
E.
,
Toyjanova
,
J.
,
Andrews
,
E.
,
Kim
,
K. S.
, and
Franck
,
C.
,
2015
, “
A Fast Iterative Digital Volume Correlation Algorithm for Large Deformations
,”
Exp. Mech.
,
55
(
1
), pp.
261
274
.10.1007/s11340-014-9874-2
16.
Madi
,
K.
,
Tozzi
,
G.
,
Zhang
,
Q. H.
,
Tong
,
J.
,
Cossey
,
A.
,
Au
,
A.
,
Hollis
,
D.
, and
Hild
,
F.
,
2013
, “
Computation of Full-Field Displacements in a Scaffold Implant Using Digital Volume Correlation and Finite Element Analysis
,”
Med. Eng. Phys.
,
35
(
9
), pp.
1298
1312
.10.1016/j.medengphy.2013.02.001
17.
Schreier
,
H. W.
, and
Sutton
,
M. A.
,
2002
, “
Systematic Errors in Digital Image Correlation Due to Undermatched Subset Shape Functions
,”
Exp. Mech.
,
42
(
3
), pp.
303
310
.10.1007/BF02410987
18.
Lu
,
H.
, and
Cary
,
P. D.
,
2000
, “
Deformation Measurements by Digital Image Correlation: Implementation of a Second-Order Displacement Gradient
,”
Exp. Mech.
,
40
(
4
), pp.
393
400
.10.1007/BF02326485
19.
Poissant
,
J.
, and
Barthelat
,
F.
,
2010
, “
A Novel ‘Subset Splitting' Procedure for Digital Image Correlation on Discontinuous Displacement Fields
,”
Exp. Mech.
,
50
(
3
), pp.
353
364
.10.1007/s11340-009-9220-2
20.
Eberl
,
C.
,
2010
, “
Digital Image Correlation and Tracking
,” The MathWorks Inc., Natick, MA, http://www.mathworks.com/matlabcentral/fileexchange/12413-digital-image-correlation-and-tracking
21.
Jones
,
E.
,
2013
, “
Improved Digital Image Correlation (DIC)
,” The MathWorks Inc., Natick, MA, http://www.mathworks.com/matlabcentral/fileexchange/43073-improved-digital-image-correlation–dic-
22.
Tseng
,
Q.
,
Duchemin-Pelletier
,
E.
,
Deshiere
,
A.
,
Balland
,
M.
,
Guillou
,
H.
,
Filhol
,
O.
, and
Théry
,
M.
,
2012
, “
Spatial Organization of the Extracellular Matrix Regulates Cell–Cell Junction Positioning
,”
Proc. Natl. Acad. Sci.
,
109
(
5
), pp.
1506
1511
.10.1073/pnas.1106377109
23.
Mori
,
N.
, and
Chang
,
K. A.
,
2003
, “
Introduction to MPIV
,” http://www.oceanwave.jp/softwares/mpiv/
24.
Blaber
,
J.
,
Adair
,
B.
, and
Antoniou
,
A.
,
2015
, “
Ncorr: Open-Source 2D Digital Image Correlation Matlab Software
,”
Exp. Mech.
,
55
(
6
), pp.
1105
1122
.10.1007/s11340-015-0009-1
25.
Bornert
,
M.
,
Brémand
,
F.
,
Doumalin
,
P.
, and
Dupré
,
J. C.
,
2009
, “
Assessment of Digital Image Correlation Measurement Errors: Methodology and Results
,”
Exp. Mech.
,
49
(
3
), pp.
353
370
.10.1007/s11340-008-9204-7
26.
Fazzini
,
M.
,
Mistou
,
S.
,
Dalverny
,
O.
, and
Robert
,
L.
,
2010
, “
Study of Image Characteristics on Digital Image Correlation Error Assessment
,”
Opt. Lasers Eng.
,
48
(
3
), pp.
335
339
.10.1016/j.optlaseng.2009.10.012
27.
Crammond
,
G.
,
Boyd
,
S.
, and
Dulieu-Barton
,
J.
,
2013
, “
Speckle Pattern Quality Assessment for Digital Image Correlation
,”
Opt. Lasers Eng.
,
51
(
12
), pp.
1368
1378
.10.1016/j.optlaseng.2013.03.014
28.
Yuan
,
Y.
,
Huang
,
J.
,
Peng
,
X.
,
Xiong
,
C.
,
Fang
,
J.
, and
Yuan
,
F.
,
2014
, “
Accurate Displacement Measurement Via a Self-Adaptive Digital Image Correlation Method Based on a Weighted ZNSSD Criterion
,”
Opt. Lasers Eng.
,
52
, pp.
75
85
.10.1016/j.optlaseng.2013.07.016
29.
Eckstein
,
A.
, and
Vlachos
,
P. P.
,
2009
, “
Assessment of Advanced Windowing Techniques for Digital Particle Image Velocimetry (DPIV)
,”
Meas. Sci. Technol.
,
20
(
7
), p.
075402
.10.1088/0957-0233/20/7/075402
30.
Westerweel
,
J.
,
Dabiri
,
D.
, and
Gharib
,
M.
,
1997
, “
The Effect of a Discrete Window Offset on the Accuracy of Cross-Correlation Analysis of Digital PIV Recordings
,”
Exp. Fluids
,
23
(
1
), pp.
20
28
.10.1007/s003480050082
31.
Huang
,
J.
,
Pan
,
X.
,
Peng
,
X.
,
Yuan
,
Y.
,
Xiong
,
C.
,
Fang
,
J.
, and
Yuan
,
F.
,
2013
, “
Digital Image Correlation With Self-Adaptive Gaussian Windows
,”
Exp. Mech.
,
53
(
3
), pp.
505
512
.10.1007/s11340-012-9639-8
32.
Rappaport
,
C.
,
2002
, “
A Color Map for Effective Black-and-White Rendering of Color Scale Images
,”
IEEE Antennas Propag. Mag.
,
44
(
3
), pp.
94
96
.10.1109/MAP.2002.1028735
33.
Landau
,
L. D.
,
Pitaevskii
,
L. P.
,
Kosevich
,
A. M.
, and
Lifshitz
,
E. M.
,
2012
,
Theory of Elasticity
,
Elsevier
,
Burlington, MA
.
34.
Bower
,
A. F.
,
2010
,
Applied Mechanics of Solids
,
CRC Press
,
Boca Raton, FL
.
35.
Franck
,
C.
,
Hong
,
S.
,
Maskarinec
,
S. A.
, and
Tirrell
,
D. A.
,
2007
, “
Three-Dimensional Full-Field Measurements of Large Deformations in Soft Materials Using Confocal Microscopy and Digital Volume Correlation
,”
Exp. Mech.
,
47
(
3
), pp.
427
438
.10.1007/s11340-007-9037-9
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