High-precision 3D shape measurement of rigid moving objects based on the Hilbert transform.

Area of Science:

• Optical Metrology
• 3D Imaging
• Computational Imaging

Background:

• Phase-shifting profilometry (PSP) is a 3D measurement technique requiring consistent object positioning.
• Accurate pixel matching in modulation patterns is crucial for successful PSP, especially for moving objects.
• Existing methods struggle with maintaining pattern quality and positional consistency under motion.

Purpose of the Study:

• To propose a generic modulation pattern enhancement method for rigid moving objects using PSP.
• To improve the signal-to-noise ratio and quality of fringe patterns for enhanced 3D measurements.
• To reduce motion-induced phase errors in the 3D reconstruction of dynamic scenes.

Main Methods:

• Utilized the Hilbert transform to suppress zero-frequency components in fringe patterns.
• Applied a hybrid digital filter to isolate and enhance positive fundamental frequency components.
• Employed a grid-based motion statistics algorithm for robust feature correspondence and pixel matching between frames.
• Implemented image clipping to ensure positional consistency of object data across multiple frames.
• Performed 3D shape reconstruction using the three-step PSP technique.

Main Results:

• The proposed method significantly enhances modulation pattern quality.
• High-precision pixel matching was achieved, even with object motion.
• A substantial reduction in motion-introduced phase error was observed.
• The technique demonstrated effectiveness in improving 3D shape reconstruction accuracy for moving objects.

Conclusions:

• The Hilbert transform-based enhancement method is effective for PSP in dynamic scenarios.
• The approach ensures high-quality modulation patterns and accurate pixel matching, crucial for 3D measurements of moving objects.
• This work contributes to more robust and precise 3D shape reconstruction in the presence of motion.