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Temporal-spatial binary encoding method based on dynamic threshold optimization for 3D shape measurement.

Pei Zhou, Xiaoyi Feng, Jun Luo

    Optics Express
    |July 21, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel spatial-temporal binary encoding method for 3D shape measurement. It enhances accuracy and reliably reconstructs moving objects by optimizing fringe patterns.

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    Area of Science:

    • Optics and Photonics
    • Computer Vision
    • Metrology

    Background:

    • Binary encoding is common for 3D shape measurement using digital mirror device (DMD) projectors.
    • Traditional methods suffer from reduced depth of field and signal-to-noise ratio (SNR) due to defocus requirements for sinusoidality.

    Purpose of the Study:

    • To propose a spatial-temporal binary encoding method with dynamic threshold optimization for improved 3D shape measurement.
    • To address limitations of traditional binary encoding in depth of field and image quality.

    Main Methods:

    • Decomposing sinusoidal fringe patterns into multiple binary patterns (K).
    • Implementing dynamic threshold determination and temporal-spatial error diffusion encoding.
    • Utilizing integral imaging for near-focused projection and approximate sinusoidal patterns.

    Main Results:

    • Achieved significant improvements in reconstruction error for planar and object measurements (13.66% and 12.57% respectively with K=2).
    • Demonstrated reliable 3D shape reconstruction of a moving object (palm) under dynamic conditions.

    Conclusions:

    • The proposed spatial-temporal binary encoding method enhances 3D shape measurement accuracy and robustness.
    • This technique offers a viable solution for high-accuracy 3D reconstruction, including dynamic scenes.