High-precision camera calibration based on a 1D target.

Area of Science:

• Computer Vision
• Robotics
• Metrology

Background:

• Traditional camera calibration often relies on complex global nonlinear optimization.
• Achieving high accuracy in 1D camera calibration presents significant challenges.
• Existing methods may struggle with distortion parameters and noise sensitivity.

Purpose of the Study:

• To develop a high-precision algorithm for camera 1D calibration.
• To improve upon existing methods by addressing distortion correction and noise robustness.
• To offer a simplified yet accurate calibration approach without global nonlinear optimization.

Main Methods:

• A novel cyclic distortion correction method is employed to refine distortion parameter estimation.
• A new criterion for nonlinear optimization of distortion correction is developed.
• Constraint equations are optimally weighted to enhance the anti-noise capability of the closed-form solution.

Main Results:

• The proposed algorithm demonstrates superior calibration accuracy and robustness.
• Performance is comparable to established 2D calibration techniques.
• The method effectively handles distortion and maintains accuracy under noisy conditions.

Conclusions:

• The developed algorithm offers a precise and robust solution for camera 1D calibration.
• It provides a new methodology for distortion correction and insights for 2D large field-of-view calibration.
• The approach simplifies calibration by avoiding global nonlinear optimization while maintaining high accuracy.