Microscope autofocus algorithm based on number of image slope variations.

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.