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Error-diffusion-kernel parameters for binary pattern in 1-bit fringe projection profilometry.

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    This study enhances fringe projection profilometry by expanding the error-diffusion kernel. The new 3x5 kernel generates 1-bit fringes with fewer harmonics, improving accuracy in 3D measurements.

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    Area of Science:

    • Optics and Photonics
    • Computer Vision and Image Processing

    Background:

    • 1-bit processing of 8-bit raster patterns is crucial for fringe projection profilometry, enabling high-speed 3D measurements and reducing nonlinear errors.
    • Generating 1-bit fringes from sinusoidal patterns inevitably introduces high-order harmonics, which can degrade measurement accuracy.

    Purpose of the Study:

    • To develop a novel method for generating 1-bit fringes with reduced high-order harmonics for fringe projection profilometry.
    • To improve the accuracy and quality of sinusoidal patterns used in 3D profilometry.

    Main Methods:

    • Expanding the error-diffusion kernel from 2x3 to 3x5 in the Floyd-Steinberg dithering algorithm.
    • Optimizing the parameters of the 3x5 error-diffusion kernel for fringe generation.
    • Simulating and experimentally validating the performance of the proposed method.

    Main Results:

    • The proposed 3x5 error-diffusion kernel generates 1-bit fringes with significantly fewer high-order harmonics compared to conventional methods.
    • Simulations demonstrate that the generated fringes are closer to sinusoidal patterns after Gaussian low-pass filtering.
    • Experimental results confirm higher measurement accuracy using the optimized 3x5 diffusion kernel.

    Conclusions:

    • The expanded 3x5 error-diffusion kernel effectively suppresses high-order harmonics in 1-bit fringe generation.
    • This method offers a significant improvement in accuracy for fringe projection profilometry applications.
    • The optimized 3x5 kernel provides a superior approach for high-speed, high-accuracy 3D measurements.