A Novel Concentric Circular Coded Target, and Its Positioning and Identifying Method for Vision Measurement under...

Area of Science:

• Computer Vision
• Metrology
• Robotics

Background:

• Coded targets are crucial for automated vision measurement tasks like 3D reconstruction.
• Existing coded targets face challenges in accuracy and efficiency under poor illumination and extreme viewing angles.

Purpose of the Study:

• To present a novel concentric circular coded target (CCCT) and its associated positioning and identification algorithms.
• To enhance the accuracy and robustness of vision measurement systems in difficult environmental conditions.

Main Methods:

• Developed a novel CCCT design.
• Implemented algorithms for eccentricity error correction using an error-compensation model.
• Utilized adaptive brightness adjustment for illumination variations.
• Applied perspective correction for robust recognition under varying viewpoints.

Main Results:

• Reduced eccentricity errors by 95% (larger circles) and 77% (smaller circles) at a 70° viewing angle.
• Decreased vision measurement error by up to 18.54% in a wing deformation experiment with corrected center positioning.
• Demonstrated high applicability and accuracy in challenging environments.

Conclusions:

• The proposed CCCT and algorithms provide accurate positioning and robust identification.
• The method effectively addresses challenges of poor illumination and wide viewing angles in vision measurement.
• The CCCT system is highly applicable for industrial vision and complex measurement tasks.