Color-encoded single-shot computer-generated Moiré profilometry

AbstractA color-encoded single-shot computer-generated Moiré profilometry (CSCGMP) is proposed. Two sinusoidal gratings with a π phase difference are encoded in red and blue channels respectively to combine a composite color grating. While this composite color grating is projected onto the measured object, the corresponding color deformed pattern can be captured. So two deformed patterns with a π phase difference are separated from its red and blue components respectively. After normalization and subtraction, the AC component of both separated deformed patterns can be extracted. If this AC component respectively multiplied by the two AC components of fringe patterns of reference plane with a π/2 phase difference prepared and saved on the computer in advance, two computer-generated Moiré fringes just respectively standing for sine and cosine of phase which is modulated by the height of the object relative to the reference plane are figured out. So the 3D shape of the measured object can be reconstructed with normal computer-generated Moiré profilometry. Both simulation and experimental results show the feasibility and validity of the proposed method. It has potential in real-time 3D measurement due to its single-shot feature.

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Computer-generated moiré profilometry based on fringe-superposition

Scientific Reports ◽

10.1038/s41598-020-74167-w ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Chengmeng Li ◽

Yiping Cao ◽

Lu Wang ◽

Yingying Wan ◽

Hongmei Li ◽

...

Keyword(s):

Phase Difference ◽

Phase Distribution ◽

Reference Plane ◽

Frequency Noise ◽

Complex Objects ◽

Measurement Capability ◽

Measured Object ◽

Moiré Fringes ◽

Dc Component ◽

Fringe Patterns

Abstract A computer-generated moiré profilometry based on algebraic addition instead of algebraic multiplication is proposed. Firstly, the two AC components of the captured fringe patterns on the reference plane with $$\pi /2$$ π / 2 phase difference are retrieved and saved in advance. While measuring, two sinusoidal gratings with $$\pi$$ π phase difference are projected onto the measured object alternatively, and the corresponding deformed patterns are captured. Then the AC component of the captured deformed pattern can be separated exactly. When the positive and negative AC component of the captured deformed pattern are added to the two prestored AC components respectively, two moiré fringes only reflect sine and cosine of the object’s phase information can be successfully generated via a series of data processing procedures. Finally, the phase distribution of the measured object can be extracted by arctangent of the ratio of these two moiré fringes. Compared with computer-generated moiré profilometry based on algebraic multiplication, this proposed method can reduce the effect of high frequency noise and residual DC component on measurement and improve the measurement accuracy. While compared with $$\pi$$ π phase shifting FTP, this method can measure more complex objects with better measurement capability. Experimental results verify the feasibility and validity of the proposed method.

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SFSSD: A Select Feature Single-shot Detector for Real-time Target detection

2020 Chinese Automation Congress (CAC) ◽

10.1109/cac51589.2020.9326960 ◽

2020 ◽

Author(s):

Shengyang Wang ◽

Zhi Li ◽

Xinpin Rao

Keyword(s):

Real Time ◽

Target Detection ◽

Single Shot

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A New Method for Phase Difference Estimation Based on Time-Varying Signal Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.333-335.650 ◽

2013 ◽

Vol 333-335 ◽

pp. 650-655

Author(s):

Peng Hui Niu ◽

Yin Lei Qin ◽

Shun Ping Qu ◽

Yang Lou

Keyword(s):

Signal Processing ◽

Real Time ◽

Phase Difference ◽

Time Signal ◽

Time Interval ◽

Time Varying ◽

Signal Model ◽

Time Frequency ◽

Mass Flowmeter ◽

Coriolis Mass Flowmeter

A new signal processing method for phase difference estimation was proposed based on time-varying signal model, whose frequency, amplitude and phase are time-varying. And then be applied Coriolis mass flowmeter signal. First, a bandpass filtering FIR filter was applied to filter the sensor output signal in order to improve SNR. Then, the signal frequency could be calculated based on short-time frequency estimation. Finally, by short window intercepting, the DTFT algorithm with negative frequency contribution was introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference obtained, the time interval of two signals was calculated. Simulation results show that the algorithms studied are efficient. Furthermore, the computation of algorithms studied is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.

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Real-time and single shot CMR increases throughput and improves reliability

Journal of Cardiovascular Magnetic Resonance ◽

10.1186/1532-429x-14-s1-p43 ◽

2012 ◽

Vol 14 (S1) ◽

Author(s):

Abdul Wattar ◽

Subha V Raman ◽

Orlando P Simonetti

Keyword(s):

Real Time ◽

Single Shot

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Single-shot detection of 8 unique monochrome fringe patterns representing 4 distinct directions via multispectral fringe projection profilometry

Scientific Reports ◽

10.1038/s41598-021-88136-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Parsa Omidi ◽

Mohamadreza Najiminaini ◽

Mamadou Diop ◽

Jeffrey J. L. Carson

Keyword(s):

Spatial Resolution ◽

Fringe Pattern ◽

Three Dimensional ◽

Fringe Projection ◽

Video Frame ◽

Single Shot ◽

Shot Detection ◽

Fringe Patterns ◽

Fringe Projection Profilometry ◽

Multispectral Camera

AbstractSpatial resolution in three-dimensional fringe projection profilometry is determined in large part by the number and spacing of fringes projected onto an object. Due to the intensity-based nature of fringe projection profilometry, fringe patterns must be generated in succession, which is time-consuming. As a result, the surface features of highly dynamic objects are difficult to measure. Here, we introduce multispectral fringe projection profilometry, a novel method that utilizes multispectral illumination to project a multispectral fringe pattern onto an object combined with a multispectral camera to detect the deformation of the fringe patterns due to the object. The multispectral camera enables the detection of 8 unique monochrome fringe patterns representing 4 distinct directions in a single snapshot. Furthermore, for each direction, the camera detects two π-phase shifted fringe patterns. Each pair of fringe patterns can be differenced to generate a differential fringe pattern that corrects for illumination offsets and mitigates the effects of glare from highly reflective surfaces. The new multispectral method solves many practical problems related to conventional fringe projection profilometry and doubles the effective spatial resolution. The method is suitable for high-quality fast 3D profilometry at video frame rates.

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