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

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Fast Three-Dimensional Profilometry with Large Depth of Field.

Wei Zhang¹, Jiongguang Zhu², Yu Han¹

¹Department of Computer Technology and Science, Anhui University of Finance and Economics, Bengbu 233030, China.

Sensors (Basel, Switzerland)

|July 13, 2024

Summary

A novel time-domain Gaussian fitting method enhances 3D imaging speed and depth of field (DoF) using neural networks. This technique offers fast, accurate 3D profilometry for complex surfaces with reduced computation time.

Keywords:

large depth of field neural network three-dimensional profilometry time-domain Gaussian fitting

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Area of Science:

Optical Engineering
Computational Imaging
Computer Vision

Background:

Binary defocusing techniques accelerate 3D imaging but suffer from limited depth of field (DoF) and sensitivity to defocus variations.
Existing 3D profilometry methods struggle with complex surfaces and require significant computation time.

Purpose of the Study:

To develop a fast and robust 3D imaging technique with an extended depth of field (DoF).
To address the limitations of existing binary defocusing methods in terms of sensitivity and DoF.
To enable accurate 3D measurement of complex surfaces.

Main Methods:

A novel time-domain Gaussian fitting method is proposed, introducing the concept of a time-domain Gaussian curve.
Neural network techniques are employed for rapid computation of time-domain Gaussian curve peak positions.
The binary defocusing technique is integrated with the neural network for enhanced 3D profilometry.

Main Results:

The proposed method extends the system's depth of field (DoF) by five times.
Both data acquisition and computation times are reduced to less than 35 milliseconds.
The method demonstrates suitability for measuring complex surfaces due to pixel-level feature extraction.

Conclusions:

The combination of binary defocusing and neural network-based time-domain Gaussian fitting achieves fast 3D profilometry with a large DoF.
The proposed technique offers significant improvements in speed, DoF, and applicability to complex surfaces.
This approach represents a substantial advancement in high-speed, large-DoF 3D imaging.