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    A new method called surface estimation via analysis method (SEAM) accurately estimates object surface profiles for ultrasonic imaging. This technique improves interior inspection of complex geometries, leading to better defect detection.

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    Area of Science:

    • Nondestructive evaluation
    • Ultrasonic imaging
    • Image processing

    Background:

    • Ultrasonic imaging is crucial for nondestructive evaluation, offering cost-effectiveness and operational safety.
    • Inspecting the interior of complex geometries necessitates accurate knowledge of object surface geometry.
    • Current surface estimation methods often rely on processing images of the water-specimen interface.

    Purpose of the Study:

    • To introduce a novel method for accurate surface profile extraction in ultrasonic testing.
    • To enhance the precision of surface estimation for complex object geometries.
    • To improve the visualization of internal defects through better surface profiling.

    Main Methods:

    • The study proposes surface estimation via analysis method (SEAM), an inverse problem-based approach.
    • SEAM incorporates priors and second-order total variation regularization to reduce noise and favor piecewise linear profiles.
    • The method processes images of the water-specimen interface to estimate surface geometry.

    Main Results:

    • SEAM demonstrated good agreement with reference data in surface profile estimation experiments.
    • The proposed method achieved lower errors compared to existing literature techniques.
    • Estimated profiles significantly improved the internal imaging of objects, aiding defect visualization.

    Conclusions:

    • SEAM provides a robust and accurate solution for surface profile estimation in ultrasonic nondestructive evaluation.
    • The method's ability to handle complex geometries and reduce noise makes it valuable for industrial inspection.
    • Improved surface estimation directly translates to enhanced internal defect detection and analysis.