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Related Experiment Video

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Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy

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Method to eliminate the zero spectra in Fourier transform profilometry based on a cost function.

Shi-lin Cui¹, Fei Tian, De-hua Li

¹Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan, China 430074. shilinc@wo.com.cn

|June 15, 2012

Summary

This study introduces a novel cost function and two algorithms for Fourier transform profilometry (FTP) to improve 3D measurement accuracy and speed. These data-driven methods effectively remove background noise, enhancing 3D measurement performance.

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Area of Science:

Optics and Photonics
Metrology and Measurement Science
Computer Vision and Image Processing

Background:

Fourier Transform Profilometry (FTP) is crucial for 3D surface measurements.
Existing FTP methods struggle with background noise and parameter tuning.
Improving accuracy, speed, and robustness in FTP remains a significant challenge.

Purpose of the Study:

To enhance the accuracy, speed, and robustness of 3D measurements in FTP.
To introduce a novel cost function tailored to amplitude and frequency modulated (AF/M) signals.
To develop data-driven algorithms for effective background component elimination in fringe patterns.

Main Methods:

A new cost function based on intrinsic AF/M signal features was developed.
Two novel algorithms were proposed to eliminate background components using the cost function.
Standard Fourier Transform (FT) was applied to calculate phase after background removal.

Main Results:

Theoretical analysis and 80 experiments validated the proposed cost function.
The two proposed methods demonstrated superior accuracy and robustness compared to wavelet-based techniques.
The new algorithms achieved approximately 70x speed improvement over 1D complex Morlet wavelet transform profilometry.

Conclusions:

The proposed cost function and algorithms significantly improve 3D measurement in FTP.
These data-driven methods offer robust performance across various fringe patterns and noise conditions.
The advancements provide a faster and more accurate solution for 3D surface metrology.