Correlation-based method for comparing and reconstructing nearly identical two-dimensional structures.

Area of Science:

• Optics
• Image Processing
• Metrology

Background:

• Comparing and reconstructing objects with minor variations is crucial in metrology and manufacturing.
• Existing methods may struggle with subtle positional differences in identical structures.

Purpose of the Study:

• To develop a robust method for comparing and reconstructing nearly identical planar objects.
• To precisely identify and locate differences, specifically a single aperture shift, between two similar structures.

Main Methods:

• A subtraction algorithm is employed for object comparison.
• Cross-correlation and autocorrelation functions are utilized to analyze structural differences.
• The method focuses on planar objects with identical apertures, differing only in one aperture's position.

Main Results:

• Simulated results confirm the feasibility of the proposed subtraction algorithm.
• The method effectively identifies discrepancies in aperture locations between nearly identical objects.
• Reconstruction of the objects based on the identified differences is demonstrated.

Conclusions:

• The developed subtraction algorithm offers a viable approach for precise comparison and reconstruction of planar objects with minor positional variations.
• This technique holds potential for quality control and defect detection in manufacturing processes involving identical components.