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Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens
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Subpixel Matching Using Double-Precision Gradient-Based Method for Digital Image Correlation.

Gang Liu1, Mengzhu Li1, Weiqing Zhang1

  • 1School of Civil Engineering, Chongqing University, No. 83 Shabei Street, Chongqing 400045, China.

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|May 5, 2021
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Summary
This summary is machine-generated.

A new double-precision gradient-based algorithm (DPG) enhances digital image correlation (DIC) for accurate displacement and strain measurement. This method significantly improves accuracy and anti-noise capabilities in subpixel analysis.

Keywords:
digital image correlationdisplacement measurementgradient-based algorithmlinear combinationsubpixel matching

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Area of Science:

  • Mechanical Engineering
  • Optical Measurement Techniques
  • Materials Science

Background:

  • Digital image correlation (DIC) is crucial for displacement and strain measurement.
  • Subpixel matching accuracy is key to reliable DIC results.
  • Existing methods face challenges with noise and precision.

Purpose of the Study:

  • To propose a novel subpixel displacement matching method for DIC.
  • To enhance accuracy and anti-noise capabilities in displacement identification.
  • To improve the overall performance of DIC techniques.

Main Methods:

  • Introduced the double-precision gradient-based algorithm (DPG) for subpixel matching.
  • Employed a coarse-fine search algorithm for integer pixel displacement.
  • Utilized five-point bicubic spline interpolation and a novel noise-aware combination coefficient.

Main Results:

  • The DPG method achieved an accuracy of 92.67%, surpassing the Newton-Raphson method.
  • Demonstrated a four-fold improvement in accuracy compared to traditional gradient-based methods.
  • Showcased superior anti-noise performance and stability in simulated and experimental tests.

Conclusions:

  • The proposed DPG algorithm offers a significant advancement in DIC accuracy and robustness.
  • DPG provides a reliable solution for precise displacement and strain analysis, even in noisy conditions.
  • This method holds potential for broader applications in experimental mechanics and material testing.