Assessment of speckle-pattern quality in digital image correlation based on gray intensity and speckle morphology

Jihyuk Park, Sungsik Yoon, Tae Hyun Kwon, Kyoungsoo Park

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

In digital image correlation (DIC), speckle patterns are generated on the surface of a specimen to resolve uniqueness issues. Thus, speckle patterns significantly affect the accuracy of image correlation. To assess the quality of speckle patterns, the standard deviation of gray intensities within each speckle (SDGIS) is introduced as a new metric. On the basis of the cumulative distribution of SDGIS, speckle-pattern quality measurement (ρ) is proposed, which integrates the features of gray intensity and speckle morphology. Twelve speckle patterns are generated by changing the spraying time and nozzle sizes of an airbrush because these are associated with the speckle volume fraction and speckle size, respectively. In addition, three displacement fields are used to investigate the effects of speckle patterns on the accuracy of the DIC results. For the 12 speckle images associated with the three displacement fields, the correlation results demonstrate that the proposed speckle-pattern quality measurement is inversely proportional to the averaged error of the subset method. This is statistically confirmed by evaluating the correlation coefficient and p-value. Furthermore, the error of the subset method is more affected by speckle patterns than the subset size when the subset size is sufficiently large.

Original languageEnglish
Pages (from-to)62-72
Number of pages11
JournalOptics and Lasers in Engineering
Volume91
DOIs
Publication statusPublished - 2017 Apr 1

Fingerprint

speckle patterns
Speckle
set theory
standard deviation
spraying
uniqueness
correlation coefficients
nozzles
Spraying
Volume fraction
Nozzles

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Mechanical Engineering
  • Electrical and Electronic Engineering

Cite this

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abstract = "In digital image correlation (DIC), speckle patterns are generated on the surface of a specimen to resolve uniqueness issues. Thus, speckle patterns significantly affect the accuracy of image correlation. To assess the quality of speckle patterns, the standard deviation of gray intensities within each speckle (SDGIS) is introduced as a new metric. On the basis of the cumulative distribution of SDGIS, speckle-pattern quality measurement (ρ) is proposed, which integrates the features of gray intensity and speckle morphology. Twelve speckle patterns are generated by changing the spraying time and nozzle sizes of an airbrush because these are associated with the speckle volume fraction and speckle size, respectively. In addition, three displacement fields are used to investigate the effects of speckle patterns on the accuracy of the DIC results. For the 12 speckle images associated with the three displacement fields, the correlation results demonstrate that the proposed speckle-pattern quality measurement is inversely proportional to the averaged error of the subset method. This is statistically confirmed by evaluating the correlation coefficient and p-value. Furthermore, the error of the subset method is more affected by speckle patterns than the subset size when the subset size is sufficiently large.",
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Assessment of speckle-pattern quality in digital image correlation based on gray intensity and speckle morphology. / Park, Jihyuk; Yoon, Sungsik; Kwon, Tae Hyun; Park, Kyoungsoo.

In: Optics and Lasers in Engineering, Vol. 91, 01.04.2017, p. 62-72.

Research output: Contribution to journalArticle

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