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    This study modified a Sagnac interferometer for diverse measurements, achieving accurate phase shifts and morphological analysis of a bee leg using optical sensing. The versatile system shows potential for microscopic applications.

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    Area of Science:

    • Optical Physics and Interferometry
    • Microscopic Imaging and Analysis
    • Deep Learning for Image Processing

    Background:

    • Traditional Sagnac interferometers have limitations in diverse measurement scenarios.
    • Adaptability and versatility are crucial for advanced optical sensing applications.
    • Need for precise phase shifting, pattern recognition, and morphological analysis in microscopic studies.

    Purpose of the Study:

    • To implement diverse modifications of the Sagnac interferometer.
    • To validate the system's adaptability for phase shifting, pattern recognition, and morphological analysis.
    • To demonstrate the potential of modified optical sensors in microscopic applications.

    Main Methods:

    • Utilized a half-wave plate (HWP) for phase shifting via multiple light reflections.
    • Introduced transparent substrates (glass, FTO) and a bee leg for pattern and morphology analysis.
    • Employed deep learning-based image processing for morphological recognition and segmentation.

    Main Results:

    • Successfully achieved phase shifts and measured hole diameters with <1.6% error.
    • Enabled separation of distinct transparent crystals and acquired morphological view of a bee's leg.
    • Attained >87% accuracy in surface area and background segmentation.

    Conclusions:

    • The modified Sagnac interferometer demonstrates significant versatility and adaptability for various measurement requirements.
    • The proposed optical sensing scheme is effective for microscopic applications, including morphological analysis.
    • The study highlights the advantages of optical sensors in precise measurement and imaging tasks.