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    Summary
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    This study introduces a novel autofocusing algorithm for laser interferometry measurements of helical tooth flanks. The method accurately identifies focused regions in interferograms, improving measurement accuracy for gear form deviations.

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    Area of Science:

    • Metrology
    • Optical Engineering
    • Mechanical Engineering

    Background:

    • Laser interferometry is crucial for measuring helical tooth flank deviations.
    • Limited depth of field (DOF) in lenses causes simultaneous focused and defocused regions in interferograms.
    • Existing autofocusing algorithms struggle to directly identify focused regions due to interference fringe impacts.

    Purpose of the Study:

    • To propose a new autofocusing algorithm for accurate identification of focused regions in interferograms.
    • To enhance the precision of helical tooth flank form deviation measurements using laser interferometry.
    • To overcome limitations of existing autofocusing methods in complex optical measurements.

    Main Methods:

    • A novel autofocusing algorithm integrating object image analysis and registration technology.
    • Reliability region evaluation based on gray level analysis.
    • Pixel correspondence determination using registration technology.
    • Focused region identification via comparison of average gray gradients in object images.

    Main Results:

    • The proposed algorithm successfully identifies the focused region in interferograms.
    • Experimental results demonstrate the feasibility and accuracy of the new autofocusing method.
    • The algorithm effectively addresses challenges posed by interference fringes and simultaneous focused/defocused regions.

    Conclusions:

    • The developed autofocusing algorithm significantly improves the accuracy of helical tooth flank measurements.
    • This method offers a reliable solution for identifying focused regions in laser interferometry, particularly for gear metrology.
    • The integration of object image analysis and registration technology provides a robust approach to autofocusing in optical measurement systems.