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Microscope autofocus algorithm based on number of image slope variations.

Jing-Feng Weng, Guo-Hao Lu, Chun-Jen Weng

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    A new passive autofocus algorithm for interferometric microscopes uses image slope variations to find the focal plane. This method excels with surface blemishes and even without fringes, matching conventional performance.

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    Area of Science:

    • Optical microscopy
    • Image processing
    • Metrology

    Background:

    • Interferometric microscopy requires precise focusing for accurate imaging.
    • Conventional autofocusing methods can struggle with surface imperfections or lack of clear fringe patterns.

    Purpose of the Study:

    • To introduce a novel passive autofocus algorithm for interferometric microscopes.
    • To evaluate the algorithm's performance against existing methods, particularly in challenging conditions.

    Main Methods:

    • The algorithm analyzes the number of slope variations within an image mask.
    • It identifies the focal plane by detecting focus-inflection points.
    • It determines fringe appearance and disappearance planes for reference.

    Main Results:

    • The proposed algorithm demonstrated autofocusing performance comparable to conventional methods.
    • It significantly outperformed zero-order interference fringe detection schemes when handling surface blemishes.
    • The algorithm proved effective even in scenarios lacking observable fringes.

    Conclusions:

    • The developed passive autofocus algorithm offers a robust solution for interferometric microscopy.
    • It provides reliable focusing capabilities across diverse sample conditions, including those with significant surface defects.
    • This method enhances the applicability of interferometric microscopy to a wider range of samples.