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A New Stitching Method for Dark-Field Surface Defects Inspection Based on Simplified Target-Tracking and Path

Xue Chen^1,2,3, Jiaqi Li^1,2,3, Yongxin Sui^1,3

¹Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.

Sensors (Basel, Switzerland)

|January 17, 2020

Summary

This study introduces a new stitching method for dark-field imaging systems, improving defect detection on large optics. The technique reduces mismatches and location errors, enhancing the identification of even weak defects.

Keywords:

dark-field imaging defect inspection image stitching scanning path correction target tracking

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Area of Science:

Optical Engineering
Metrology
Surface Science

Background:

Camera-based dark-field imaging systems detect micron-scale defects on large optics via scanning and stitching.
Conventional stitching methods struggle with mismatches and location deviations due to sparse defect distribution.

Purpose of the Study:

To develop a highly efficient stitching method for dark-field imaging systems.
To overcome limitations of conventional stitching, specifically mismatches and location deviations.
To enhance the detectability of micron-scale defects on large optical surfaces.

Main Methods:

Proposed a simplified target-tracking and adaptive scanning path correction method.
Treated defects as moving targets by increasing sub-apertures and switching camera perspective.
Implemented target tracking for marked targets and corrected scanning paths by minimizing deviations.
Updated final stitching results using the target-tracking method.

Main Results:

Successfully identified 118 out of 120 defects on a specially designed testing sample.
Achieved defect detection without stitching mismatches.
Demonstrated reduction in mismatches and location deviations.
Showcased increased detectability for weak defects.

Conclusions:

The proposed target-tracking and adaptive scanning path correction method significantly improves stitching accuracy in dark-field imaging.
This approach effectively minimizes mismatches and location deviations, crucial for defect detection on large optics.
The method enhances the overall detectability of micron-scale defects, including subtle ones.