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    This study introduces a new sub-pixel displacement measurement technique using the gray wolf optimizer (GWO) and gradient algorithm for digital speckle correlation method (DSCM). The method accurately measures deformation in rigid bodies using both synthetic and real images.

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    Area of Science:

    • Optical Metrology
    • Image Correlation
    • Computational Mechanics

    Background:

    • Digital Speckle Correlation Method (DSCM) is a key optical metrology technique for deformation analysis.
    • Accurate sub-pixel displacement measurement is crucial for precise deformation analysis.
    • Metaheuristic algorithms offer powerful optimization capabilities for complex search spaces in optical engineering.

    Purpose of the Study:

    • To propose a novel sub-pixel displacement measurement technique for DSCM.
    • To integrate the Gray Wolf Optimizer (GWO) with a gradient algorithm for enhanced accuracy.
    • To validate the proposed method's effectiveness in measuring rigid body displacement and deformation.

    Main Methods:

    • Utilizing zero-mean normalized cross-correlation for subset analysis between reference and deformed images.
    • Employing the Gray Wolf Optimizer (GWO) for initial integer pixel displacement estimation.
    • Applying a Barron gradient algorithm for final sub-pixel displacement refinement.

    Main Results:

    • The proposed GWO-gradient based DSCM method achieved effective sub-pixel displacement measurement.
    • Demonstrated superior performance compared to state-of-the-art methods on synthetic speckle images.
    • Experimental validation on real images confirmed the framework's practical effectiveness.

    Conclusions:

    • The integrated GWO and gradient algorithm provides a robust and accurate approach for sub-pixel displacement measurement in DSCM.
    • This method enhances the precision of deformation analysis in optical metrology.
    • The framework shows significant potential for applications in engineering and material science.