Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

The Phase Rule

The Phase Rule

The phase rule describes the relationship between the variance (degrees of freedom), the number of components, and the number of phases in a system at equilibrium.Variance is a concept that denotes the number of independent intensive properties (properties are those that do not depend on the amount of material in the system), such as temperature, pressure, and composition, that can be altered without impacting the number of phases in equilibrium.In a single-component system, such as pure water,...

Trapezoidal Rule

Trapezoidal Rule

Estimating the distance traveled by a vehicle using its recorded velocity over time is a common problem in physics and engineering. When velocity data is available at discrete time intervals, rather than as a continuous function, numerical integration methods such as the trapezoidal rule are often employed to approximate the total displacement.The trapezoidal rule works by dividing the total time interval into several equal segments. Within each segment, the recorded velocities at the endpoints...

Errors in Taping

Errors in Taping

Errors in taping arise from multiple factors that can significantly impact measurement accuracy in surveying. Misalignment of the tape, often due to human error, is one primary source. A skilled rear tapeman, using a telescope, can help correct alignment by guiding the head tapeman; however, human limitations still lead to small inaccuracies. These errors may include misplacement of pins or inaccurate tape readings due to common visual confusions, such as mistaking a six for a nine. Such...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Altered peripheral blood mRNA and salivary biomarkers in dental anxiety: a cross-sectional study.

BMC oral health·2026

Same author

Tracheal delivery of HO-1-modified human umbilical cord-derived mesenchymal stem cells treats pulmonary arterial hypertension by enhancing pulmonary antioxidant and anti-inflammatory responses.

Translational research : the journal of laboratory and clinical medicine·2026

Same author

Study of event-related potentials to identify differences in verbal working memory in patients with mild cognitive impairment with different Traditional Chinese Medicine syndromes.

Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan·2026

Same author

Correction: Elucidating the growth-promoting factors of Bacillus amyloliquefaciens on rapeseed through metabolomics.

BMC plant biology·2025

Same author

Optimization of the oxygen-induced retinopathy model in mice and its impact on retinal angiogenesis.

Experimental eye research·2025

Same author

Extreme climate and human interventions driving flood dynamics in arid inland rivers: regional and global perspectives.

Journal of environmental management·2025

Search research articles

Related Experiment Video

Updated: May 19, 2026

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

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

Published on: December 3, 2013

Flexible error-reduction method for shape measurement by temporal phase unwrapping: phase averaging method.

Liu Yong¹, Huang Dingfa, Jiang Yong

¹School of Civil Engineering, Southwest Jiaotong University, Cheng Du, China. liuyong@swust.edu.cn

|August 4, 2012

Summary

This summary is machine-generated.

This study introduces a phase averaging method (PAM) to reduce errors in temporal phase unwrapping for structured light shape measurement. PAM improves accuracy by averaging phases and reducing both random and nonlinear errors.

More Related Videos

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

Published on: February 23, 2018

Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

Published on: July 5, 2016

Related Experiment Videos

Last Updated: May 19, 2026

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

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

Published on: December 3, 2013

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

Published on: February 23, 2018

Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

Published on: July 5, 2016

Area of Science:

Optics and Photonics
Metrology
Computer Vision

Background:

Temporal phase unwrapping is crucial for 3D shape measurement using structured light projection.
Measurement errors in temporal phase unwrapping stem from camera noise and nonlinearities.
Least-squares fitting reduces random errors but not nonlinear errors effectively.

Purpose of the Study:

To develop an improved temporal phase unwrapping algorithm that minimizes both random and systematic errors.
To enhance the accuracy of shape measurement in structured light projection systems.

Main Methods:

Proposed a novel phase averaging method (PAM) for temporal phase unwrapping.
Incorporated an additional fringe sequence with the highest fringe density.
Optimized phase offsets within four frames based on nonlinear error periods.
Utilized statistical averaging for error reduction.

Main Results:

The proposed PAM effectively decreases both random and systematic errors.
The method demonstrates improved accuracy in temporal phase unwrapping.
Flexibility in adjusting the additional fringe sequence length allows for adaptable precision.

Conclusions:

The phase averaging method (PAM) offers a significant improvement over existing algorithms for temporal phase unwrapping.
PAM provides a robust solution for accurate 3D shape measurement in structured light systems.
Theoretical analysis and simulations validate the effectiveness of the proposed method.