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Adaptive fringe-pattern projection for image saturation avoidance in 3D surface-shape measurement.

Dong Li, Jonathan Kofman

    Optics Express
    |May 3, 2014
    PubMed
    Summary

    Adaptive fringe-pattern projection (AFPP) enhances 3D surface measurement accuracy by adjusting projected light intensity to object reflectivity, preventing image saturation and errors. This method improves 3D shape measurement even on surfaces with varying reflectivity.

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    Area of Science:

    • Optics
    • Computer Vision
    • Metrology

    Background:

    • Image saturation in fringe-projection 3D surface-shape measurement causes intensity errors, leading to inaccurate phase and measurement results.
    • Varying object surface reflectivity poses a significant challenge for traditional fringe projection methods, often resulting in data loss or reduced accuracy.

    Purpose of the Study:

    • To develop an adaptive fringe-pattern projection (AFPP) method to mitigate image saturation and improve 3D measurement accuracy.
    • To adapt the maximum input gray level of projected fringe patterns to the local reflectivity of the object surface.

    Main Methods:

    • An adaptive fringe-pattern projection (AFPP) method was developed.
    • The method adjusts the maximum input gray level based on local surface reflectivity.
    • It utilizes two prior rounds of fringe projection and image capture to generate adapted patterns.

    Main Results:

    • The AFPP method successfully avoided image saturation in highly reflective surface regions.
    • It maintained high intensity modulation across the entire object surface.
    • Improved 3D measurement accuracy was demonstrated compared to traditional methods.

    Conclusions:

    • The AFPP method effectively addresses image saturation and varying surface reflectivity in fringe-projection 3D measurements.
    • This technique offers enhanced accuracy and robustness for 3D surface-shape measurement applications.