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Iterative camera calibration method using ray tracing and entrance pupil center constraints for phase measuring
Applied Optics
|March 17, 2026
Summary
This study presents an iterative camera calibration method for precise 3D measurement. The technique enhances accuracy by using ray tracing and entrance pupil constraints, significantly reducing reconstruction errors.
Area of Science:
- Optics and Photonics
- Metrology
- Computer Vision
Background:
- High-precision 3D measurement demands accurate camera calibration.
- Existing methods face challenges in achieving sufficient accuracy.
Purpose of the Study:
- To propose an iterative camera calibration method for improved accuracy in 3D measurement.
- To introduce entrance pupil center constraints and outlier removal for enhanced precision.
Main Methods:
- An iterative approach utilizing ray tracing to estimate the entrance pupil center.
- Incorporation of entrance pupil center as a constraint in calibration.
- Outlier control point removal using the 3-sigma criterion.
- Iterative optimization of vision ray parameters via the Levenberg-Marquardt algorithm.
Main Results:
- Significant reduction in reconstruction error for a 120 mm metal bearing.
- Root Mean Square (RMS) error decreased from 0.20 mm to 0.07 mm.
- Peak-to-Valley (PV) error reduced from 1.39 mm to 0.76 mm.
Conclusions:
- The proposed iterative method achieves high accuracy in 3D measurement.
- The method's performance approaches that of coordinate measuring machines.
- This technique offers a viable solution for accurate camera calibration in demanding applications.
