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Fringe-projection profilometry based on two-dimensional empirical mode decomposition.

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    Summary
    This summary is machine-generated.

    A novel 2D empirical mode decomposition (2D-EMD) method enhances 3D shape measurement by effectively reducing noise and background intensity in fringe patterns. This technique improves phase retrieval accuracy and processing speed for 3D profilometry.

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    Area of Science:

    • Optics and Photonics
    • Computer Vision
    • Metrology

    Background:

    • Fringe-projection profilometry is crucial for 3D shape measurement.
    • Deformed fringe patterns often suffer from noise and background intensity, degrading measurement accuracy.
    • Existing methods struggle with low-frequency information and noise reduction.

    Purpose of the Study:

    • To propose a novel fringe-projection profilometry method using 2D empirical mode decomposition (2D-EMD).
    • To address challenges of noise and background intensity in deformed fringe patterns for improved 3D shape measurement.
    • To enhance phase retrieval accuracy and reduce processing time in 3D profilometry.

    Main Methods:

    • Decomposition of fringe patterns into intrinsic mode functions using 2D-EMD.
    • Partial noise reduction and removal of background components.
    • Hilbert transformation applied to fundamental components for phase retrieval.
    • Full 2D analysis considering adjacent fringe lines for modulation phase extraction.

    Main Results:

    • Effective extraction of modulation phase for single-direction and inclined fringe patterns.
    • Significant reduction of noise and background intensity.
    • Shortened data processing time compared to ensemble EMD.
    • Feasibility demonstrated through computer simulations and experimental validation.

    Conclusions:

    • The proposed 2D-EMD based fringe-projection profilometry method is effective for 3D shape measurement.
    • This approach offers improved accuracy and efficiency in phase retrieval.
    • The method successfully handles noise and background complexities in fringe patterns.