A Review on Deformation Measurement from Speckle Patterns using Digital Image Correlation

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022 www.irjet.net p-ISSN: 2395-0072
© 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 3528
A Review on Deformation Measurement from Speckle Patterns using
Digital Image Correlation
Haleema S. H. 1, Dr. Naveen S. 2, Dr. Deepambika V. A. 3
1PG Student, Dept. of Electronics & Communication Engineering, LBSITW, Kerala, India
2Assistant Professor, Dept. of Electronics & Communication Engineering, LBSITW, Kerala, India
3Assistant Professor, Dept. of Electronics & Communication Engineering, LBSITW, Kerala, India
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Abstract - The deformation measurement of a structural
element subjected to external loads at any point is vital in
several engineering domains such as mechanical, civil,
aerospace, etc. For example, in the fields of mechanical
engineering and civil engineering, the deformation properties
are evaluated by measuring the surface displacement under a
given load and structural stability is assessed by measuring
the whole deformation of concrete and steel structures under
load respectively. The conventional instruments that measure
strain such as strain gauges, extensometers, etc. cannotcreate
strain maps. A full-field strain measurement is possible with
digital image correlation (DIC), a non-contact optical
deformation measurementtechnology. TheDICmethod'smain
premise is to collect speckle images that are naturally carried
or purposefully created on an object's surface beforeandafter
deformation and convert them into a gray image. This
measurement method is easy to use, belongs to the non-
contact measurement category, and has a high level of
accuracy.
Key Words: Digital image correlation, speckle images,
deformation measurement
1. INTRODUCTION
The determination of mechanical characteristics in various
materials necessitates the use of appropriate strain
measuring techniques. This isparticularlytruewhenloading
circumstances resultincomplexheterogeneousdeformation
fields. Full field measurement techniques, in particular the
Digital Image Correlation (DIC) methodology,arewell suited
to this task. This technique, also known as the white light
speckle technique, is an optical-numerical full-field
measuring technique thatusesa comparisonofimagestaken
with a digital Charge Coupled Device (CCD) camera at
different load steps to determine in-plane displacement
fields at the surface of objects under any kind of loading. The
primary concept of the DIC method is to collect speckle
images on an object's surface that are naturally transported
or purposely formed before and after deformation and
convert them into a grayscale image.
The DIC has been widely used in material testing where the
specimen size is small and the experimental setup is well-
known. Due to its benefit over point-wise measurement
techniques it allow a vast area of structures to be measured
efficiently from a distance and the DIC has gained increased
favour in large-scale structural testing in recent years.
Three-dimensional (3D) DIC works by computing a
correlation function between two gray-scaleimagestakenat
distinct time intervals before and after deformation. From
the coordinates of captured images and the camera
calibration process, the true spatial coordinates of locations
before and after deformation are rebuilt. High spatial
resolution charge-coupled device (CCD) or complementary
metal oxide semiconductor (CMOS) cameras, camera tripod
supports, optical lenses, lighting system, camera
synchronization unit, speckle pattern, and computer with
appropriate software for displaying post-processing and
storing data are needed for 3D-DIC measurements.
2. REVIEW OF RELATED WORKS
The method of implementing digital image correlation was
first described in 1983 by Sutton et al. [1]. The authors
describe how digital imagesofanobjectaretakenbeforeand
after being transformed and use generated light intensity
levels to transform distinct data into a continuous form
through a surface fit.
To increase the accuracy of the DIC method, Bruck et al. [2]
introduced the Newton-Raphson method of partial
differential corrections and it is used to increase the
accuracy of displacement and gradient calculations. The
Newton-Raphson method is based on the calculation of
correction terms that improve the initial assumptions of the
DIC algorithm. By using the displacement of a subset center
calculated within a pixel, the algorithm is less likely to find a
local minimum, and more likely to find an absolute
minimum.
D. Lecompte et al. [3] compare three different speckle
patterns that originate from the same reference speckle
pattern and introducesa methodfordeterminingthespeckle
size distribution of speckle patterns using morphology. The
results shows that the size of the speckle along with the size
of the pixel subset used, clearly affects the accuracy of the
measured displacements.

The optimized Newton-Raphsonalgorithm wasusedby Bing
Pan et al. [4] to study the tensile test of thin aluminumplates
with circular holes, and the full field strain information was
effectively extracted from the actual displacement field data
of the DIC method. The calculation results are consistent
with the theoretical method.
Bing Pan et al. [5] proposed digital image correlation (DIC)
method using iterative least squares algorithm (ILS) for
displacement field measurement and point-wise least
squares algorithm (PLS) for strainfieldmeasurement.InILS,
correlation function concept is not used. But algorithm is
actually equal to the optimization of the sum of squared
difference correlation function using improved Newton–
Raphson method.
The mean gray intensity gradient also introduced by Bing
Pan et al. [6] for quality evaluation of the speckle patterns
used in DIC. To test this concept, five different speckle
patterns were translated numerically,andthedisplacements
measured using DIC were comparedwiththeexactones. The
errors are evaluated based on mean bias error and standard
deviation error and found that they are closely relatedtothe
mean gray intensity gradient of the specklepatternused and
a good speckle pattern has a large mean gray intensity
gradient.
Xiang Guo et al. [7] used a three-dimensional (3D) digital
image correlation using plasma spray for speckle
preparation in which a bandpass filter, neutral density
filters, and a linear polarizing filter are used to reduce
intensity and noise in images to measure the full-field strain
of the surface at 2600°C. The results show that the proposed
model is easy to implement and has high accuracy in high-
temperature deformation measurement.
To reduce the effect of electromagnetic waves radiated by
high temperature on the image, H. Deng et al. [8] placed a
bandpass filter in front of the camera lens. .Twocamerasare
needed to take images before and after deformation.3D-DIC
was used to get the deformation field.
Tianci Hu et al. [9] proposed multi-camera based full-field
3D displacement measurement using DIC. This method
needs only a small overlap area between the cameras and
doesn’t require additional calibration steps. By subtracting
the coordinates before and after translation the full-field
displacement was attained.
Y. Ding et al. [10] compare different correlation function
models and studies the performance and unimodality of the
shape function and associated functions, and the best
function model is determined. Also analyzed the three
whole-pixel search algorithmssuchas point-by-pointsearch
method, hill-climbing method and differential evolution
algorithm. It was found that the hill climbing method based
on the zero mean normalized least square distance sum
function has the best performance and accuracy.
3. SPECKLE PATTERN
A speckle pattern is a random granular pattern created by a
coherent light beam, such as a laser, reflecting off a rough
surface such as a metallic surface, a display screen, white
paint, or a sheet of paper. An example of speckle pattern is
shown in fig 1.
The interference of reflected incident light beams with the
corresponding optical phasescausesthispattern.Evenwhen
modest changes in the incident beam directionorthelighted
spot occur, the shape of the speckle pattern tends to shift.
Fig 1: Speckle pattern
3.1 Speckle Patterns Types
The following are the two primaryformsofspecklepatterns:
Subjective speckle pattern – Subjective speckle pattern
refers to speckle patterns created at the image plane of a
lens. Interference of waves from various scattering regions
of a resolution element of the lens causes subjective
patterns. The response functions of the randomlyde-phased
waves are combined in this region, resulting in speckle
patterns.
Objective speckle pattern - The formation of objective
speckle patterns occurs whena diffuseobjectisirradiatedby
a coherent wave. The size of the speckle pattern is
determined by the interference between waves from
different scattering sites. With increasing distance between
an observation plane and an item, the size grows linearly.
The surface speckle field of an object will alterin responseto
its deformation. The in-plane deformationinformationofthe
object surface can be retrieved indirectly by evaluating the
change information of the speckle field before and after
deformation. Surface polishing, artificial painting, and
speckle transfer can be used to create artificial speckle if the
object's surface lacks speckle or the quality of the speckle is
inadequate.

4. DIGITAL IMAGE CORRELATION
The 2D DIC works on the idea of collecting the speckle
images that are naturally carried or purposefully created on
the object’s surfaces before and after deformation then
converting them to a gray image. Image taken before and
after deformation is termed as the reference image and the
target image respectively. To examine and quantify the
correlation of the grayscaleinformationinthespeckleimage,
the correlation search technique is utilized. To gettheobject
surface deformation information, complete the maximum
gray field sub-region matching.
Image capture module (CCD camera, electron microscope,
and other optical imaging equipment), light source (white
light source), and DIC analysis processing module make up
the 2D-DIC image acquisition technique (computer with
built-in image processing and DIC algorithm program).Fig 2
reperesents the image acquisition module of 2D-DIC.
Fig 2: 2D-DIC Image acquisition module
During the DIC measurement procedure, the image
acquisition device's location should be kept constant,andits
optical axis should be perpendiculartothemeasuredsurface
and aligned with the measured surface's centre area. Adjust
the focal length of the lens at the same time to make the
speckle field of the surface under test clear and occupy the
majority of the image. The procedure described above can
significantly increase the accuracy of DIC measurement
findings
4.1 Mathematical Model
The random speckle pattern is used in the digital image
correlation approach to perfectly match the corresponding
locations on two images. The reference image is on the left,
while the deformed image is on the right in Fig. 3.
Fig 3: Basic principle of digital image correlation
A reference subset of (2M + 1)*(2M + 1) pixels centred at
point (x, y) is selected in the reference image. The matching
technique involves finding the appropriate subset in the
deformed image centred at point (x', y') that has thegreatest
similarity to the reference subset. Clearly, the grey level
relationship in the reference image remains the same in the
deformed image.
5. CONCLUSIONS
Digital image correlation is an optical full-field deformation
measurement technique and is widely utilized in civil
engineering, aerospace, and other sectors due to its non-
contact, high-precision, full-field characteristics. The DIC
measurement system's basic principle is to use image
acquisition equipment to collect natural texturesorartificial
speckles on the surface of the test piece before and after
deformation, then use a computer design algorithm to solve
the in-plane displacement value of each point on the surface
using the relationship between the grey scale change of the
speckle image and the surface displacement. This
measurement method is easy to use and belongs to the non-
contact measurement category, thus it may do full-field
measurements and provide a widermeasurementrangeand
greater accuracy.
ACKNOWLEDGEMENT
We would like to thank the Director ofLBSITWandPrincipal
of the institution for providing the facilities and support for
our work.
REFERENCES
[1] Sutton, M.A., Wolters, W.J., Peters, W.H., Ranson, W.F.,
McNeill, S.R.; Determination of displacements using an
improved digital correlation method. Image Vision
Computing 1983, 1(3), 133–139.
[2] Hugh Bruck; S. R. McNeill; M. A. Sutton; W. H. Peters;
Digital image correlation using Newton-Raphson
method of partial differential correction. Experimental
Mechanics 1989, 29, 261-267, 10.1007/bf02321405.
[3] D. Lecompte, A. Smits, Sven Bossuyt,H.Sol,J.Vantomme,
D. Van Hemelrijck, A.M. Habraken, Qualityassessmentof

speckle patterns fordigital imagecorrelation,Opticsand
Lasers in Engineering, Volume 44, Issue 11, 2006, Pages
1132-1145.
[4] Bing pan, Huimin Xie. Full-Field Strain Measurement
Based on Least-Square Fitting of Local Displacementfor
Digital Image Correlation Method[J]. Acta Optica Sinica,
2007, 27(11): 1980-1986.
[5] Bing Pan, Anand Asundi, Huimin Xie, Jianxin Gao, Digital
image correlation using iterative least squares and
pointwise least squaresfordisplacementfieldandstrain
field measurements, Optics and Lasers in Engineering,
Volume 47, Issues 7–8, 2009, Pages 865-874.
[6] Bing Pan, Dafang Wu, Yong, Xia. “Study of Speckle
Pattern Quality Assessment used in Digital Image
Correlation”. Journal of Experimental Mechanics , 2010,
25(02) page no: 120-129.
[7] Xiang Guo, Jin Liang, Zhengzong Tang, Binggang Cao, &
Miao Yu (2014). High-Temperature Digital Image
Correlation Method for Full-Field Deformation
Measurement Captured With Filters at 2600°C Using
Spraying to Form Speckle Patterns. Optical Engineering.
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BIOGRAPHIES
Haleema S. H., currentlypursuing M.Tech
in Signal Processing at LBS Institute of
Technology for Women, Poojappura.
Affiliated to the APJ Abdul Kalam
Technological University, Kerala. She
received her B.Tech (ECE) degree from
the University of Kerala.
Dr. Naveen S., is currently Assistant
Professor (ECE) at the LBS Institute of
Technology for Women, Poojappura,
Affiliated to the APJ Abdul Kalam
Technological University, Kerala. Hehas
taken his B. Tech in ECE, M. Tech in
Signal ProcessingandPh.DinElectronics
and Communication Engineering in the
year 2006, 2008 and 2017 respectively
from the University of Kerala. He has
published his papers in several
international journals and conferences.
Dr. Deepambika V. A., Assistant
Professor at LBS Institute of Technology
for Women, Poojappura. Affiliated to the
APJ Abdul Kalam Technological
University, Kerala.

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