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Automatic scratch detector for optical surface.

Hong-Yan Zhang, Zi-Hao Wang, Hai-Yan Fu

    Optics Express
    |September 13, 2019
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces an automated scratch detection method for optical surfaces using machine vision inspection (MVI). The new algorithm offers high accuracy and efficiency for non-destructive testing of glass-like materials.

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    Area of Science:

    • Optical Engineering
    • Materials Science
    • Metrology

    Background:

    • Scratches on optical components significantly degrade optical system performance, affecting imaging quality and light-gathering capabilities.
    • Current scratch assessment relies on human visual inspection (HVI), which is inefficient and prone to inaccuracies.
    • Quantitative analysis of scratch size is crucial for assessing their impact on optical systems.

    Purpose of the Study:

    • To develop an automated scratch detection method for optical surfaces.
    • To improve the efficiency and accuracy of scratch size assessment.
    • To enable non-destructive testing (NDT) of glass-like surfaces.

    Main Methods:

    • Utilized a microscopic dark-field scattering imaging system as the front-end detection apparatus.
    • Developed a dedicated algorithm for non-occluded scratch detection.
    • Implemented automatic processing including positioning, clustering, and precise length estimation of scratches.

    Main Results:

    • The automated method demonstrated high efficiency, processing a 2724x2724 pixel image in approximately 0.138 seconds.
    • Achieved high accuracy, with a scratch length detection error rate below 5% compared to HVI.
    • The algorithm successfully performed automatic positioning, clustering, and length estimation of scratches.

    Conclusions:

    • The proposed machine vision inspection (MVI) method provides an efficient and accurate solution for scratch detection on optical surfaces.
    • This automated approach overcomes the limitations of traditional human visual inspection (HVI).
    • The developed algorithm is suitable for non-destructive testing (NDT) applications on glass-like materials.