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Related Experiment Video

Updated: May 28, 2025

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

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Dynamic 3D Measurement Based on Camera-Pixel Mismatch Correction and Hilbert Transform.

Xingfan Chen¹, Qican Zhang¹, Yajun Wang¹

¹Department of Opto-Electronics, Sichuan University, Chengdu 610065, China.

Sensors (Basel, Switzerland)

|February 13, 2025

Summary

This summary is machine-generated.

This study introduces a universal algorithm to correct motion errors in 3D measurements. It accurately reconstructs objects even with complex, combined motions, improving 3D measurement precision.

Keywords:

3D measurement Hilbert transform dynamic measurement pixel mismatch correction

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Area of Science:

3D Measurement and Reconstruction
Computer Vision
Metrology

Background:

Object motion during 3D measurement introduces significant errors, challenging high-precision reconstruction.
Existing algorithms primarily address motion along the camera's principal axis (Z-direction), limiting their use in complex real-world scenarios.

Purpose of the Study:

To develop a universal motion error compensation algorithm for accurate 3D measurements under dynamic conditions.
To address both pixel mismatch and phase-shift errors caused by complex object motions.

Main Methods:

Correcting pixel mismatch errors using adjacent coarse 3D point cloud data.
Eliminating motion-induced phase errors via the Hilbert transform to shift fringes by π/2.
Simultaneously compensating for camera-pixel mismatch and phase-shift errors in 3D coordinate space.

Main Results:

The algorithm effectively corrects pixel mismatch and phase-shift errors.
Accurate 3D measurements are achieved even with dynamic and multidirectional object motions.
Experimental validation confirms the algorithm's robustness and broad applicability.

Conclusions:

The proposed method offers a systematic solution for motion error compensation in 3D measurement.
This advancement enhances the reliability and precision of 3D reconstruction in dynamic environments.
The algorithm is suitable for industrial inspection, biomedical imaging, and real-time robotics.