High-quality defocusing phase-shifting profilometry on dynamic objects

Guo, Yifan; Da, Feipeng; Yu, Yi

doi:10.1117/1.oe.57.10.105105

Cited by 14 publications

(5 citation statements)

References 31 publications

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“…Since the three frequency four step phase shift method is adopted in this paper, after collecting three groups of frequencies and four projective compensation images in each group, three structural grating wrapping phase graphs with period i, j and h are calculated, and pairwise superposition calculation is performed according to the adjacent sequence of period. The superimposed wrapped phase frequency l is shown in formula (24), it represents the reciprocal of the alternating number of bright and dark gratings in the projection image, it can be obtained from the horizontal resolution m of the image and the grating period T, and its value can be dynamically adjusted with the chatter phase error through the adaptively grating period proposed in this article.…”

Section: ) Inter-frame Phase Value Compensation Of the Projected Pixe...mentioning

confidence: 99%

“…Other scholars used composite algorithms for dynamic phase compensation. For example, Guo 24 calculated the motion speed of the measured object through an optical flow algorithm of visual motion detection, and then the phase value was compensated through the movement speed to realize face reconstruction in motion. The main limitation of this method is that the measured object needs to have obvious feature points; otherwise, the motion estimation of the optical flow method will contain errors.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research on error compensation method of topography dynamic reconstruction of chattering thin-walled parts based on structured light detection

Li,

Lv,

Liu

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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In order to achieve visual measurement error compensation for the surface of thin-walled components with chatter, a new real-time adaptive correction method for chatter motion error is proposed in this paper. Firstly, according to the mechanism of the chatter effect, an error analysis model of the dynamic structured light phase principal value is derived. Then, a real-time optimization method for the motion phase error in the frame of structured light projection is proposed. Meanwhile, a compensation method based on an adaptive grating projection period is proposed to eliminate the cumulative error of inter-frame chatter motion. Finally, a structured light visual inspection system and an experimental platform for chattering thin-walled parts are established for experimental verification. The experimental results under slight and severe chatter conditions indicate that the proposed method can optimize the phase errors within the projected frame in real time under any scenario, compensate for the cumulative errors between projected frames, and improve the point cloud accuracy of real-time 3D reconstruction.

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Section: ) Inter-frame Phase Value Compensation Of the Projected Pixe...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on error compensation method of topography dynamic reconstruction of chattering thin-walled parts based on structured light detection

Li,

Lv,

Liu

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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show abstract

“…However, errors caused by the movement of the objects when using PSP can lead to a decrease in measurement accuracy, affecting the results of 3D reconstruction. [10][11][12][13] To effectively eliminate motion-induced errors, Liu et al 14 proposed using motion-induced compensation to reduce motion-induced errors, but this method is only applicable when the object is moving on a plane. Huang et al 15 proposed color fringe projection, but this method requires high color requirements for the object.…”

Section: Introductionmentioning

confidence: 99%

Method for measuring the three-dimensional profile of moving objects based on neural network position transformation

Wu,

Di,

Guo

et al. 2024

Opt. Eng.

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To eliminate motion-induced errors, a multi-step fitting position transformation method is proposed for measuring the three-dimensional (3D) profile of an object. The method employs a neural network to perform position transformation on the objects in the captured motion phase-shifting fringe projection images, aligning them to the same position, and then uses the phase-shifting method to obtain the 3D profile of the objects. Theoretically, the rigid body motion transformation matrix is used to deduce the change of points on the objects in the fringe pattern under different motion conditions, and the 3D profile measurement results of randomly moving objects are simulated and analyzed. Experimentally, a neural network model was trained by using 5000 sets of data obtained from experiments to eliminate motioninduced errors in various motion states. Simulation and experimental results show that this method significantly reduces the motion-induced errors that occur when measuring moving objects using the traditional phase-shifting method. It has broad application prospects in the field of real-time measurement of moving objects' 3D profiles.

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“…Gray code, and realized high-speed measurement of moving objects. Yifan Guo et al [10] estimate motion from object images starting and ending states. Based on the phase map and the obtained initial displacement data, the displacement inversion is performed for each point, and then the phase jump caused by the motion of the object is compensated.…”

Section: Introductionmentioning

confidence: 99%

3D reconstruction of moving object by double sampling based on phase shifting profilometry

Li¹,

Lu²,

Pan³

et al. 2023

Ninth Symposium on Novel Photoelectronic Detection Technology and Applications

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High-quality defocusing phase-shifting profilometry on dynamic objects

Cited by 14 publications

References 31 publications

Research on error compensation method of topography dynamic reconstruction of chattering thin-walled parts based on structured light detection

Research on error compensation method of topography dynamic reconstruction of chattering thin-walled parts based on structured light detection

Method for measuring the three-dimensional profile of moving objects based on neural network position transformation

3D reconstruction of moving object by double sampling based on phase shifting profilometry

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