Gamma estimation method based on phase error coefficients vector in digital fringe projection system

Wang, Jie; Xin, Yu; Shi, Xuelei; Chen, Jie; Tang, Tianhang; Tang, Zixin; Liu, Yiguang

doi:10.1016/j.ijleo.2023.170624

Cited by 2 publications

(2 citation statements)

References 21 publications

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“…Compared to FTP, PSP offers significant improvements in spatial resolution and phase measurement. PSP is also more robust to changes in external light and the reflectivity of the target surface [6]. In practice, PSP typically involves using a focused projector to generate a series of sinusoidal stripes and project them onto the measured object.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional measurement based on equal spacing binary fringe coding

Yan,

Wu,

Sun

et al. 2024

Meas. Sci. Technol.

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Binary fringe projection technology can effectively avoid the measurement error caused by nonlinearity in structured light three-dimensional measurement system. In this paper, a binary fringe projection coding based on equal spacing is proposed Firstly, the image sequence projected by binary fringes with equal spacing is corresponding to the sinusoidal intensity values in the same period one by one, and then the sinusoidal fringes are generated by weighted superposition. The experimental results show that, compared with the traditional four-step and 12-step phase shifting methods, the mean square error of the synthesized sinusoidal pattern is reduced by 36.74% and 18.24% respectively, and the mean square error of the distance between the obtained spherical point cloud of the standard sphere and the center of the fitting standard sphere is reduced by 89.36% and 77.27% respectively.

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Section: Introductionmentioning

confidence: 99%

Three-dimensional measurement based on equal spacing binary fringe coding

Yan,

Wu,

Sun

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…Structured light 3D imaging with digital fringe projection has gained significant popularity in various fields, including robotics, industrial inspection, and human-computer interaction et al [1][2][3]. Phase extraction and unwrapping are inevitable and important steps in the phase-based structured light.…”

Section: Introductionmentioning

confidence: 99%

Robust structured light 3D imaging with two fringe patterns using recurrent classification neural network

Yang,

Liu,

Tang

et al. 2023

Meas. Sci. Technol.

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Robust and accurate 3D reconstruction using a limited number of fringe patterns has posed a challenge in the field of structured light 3D imaging. Unlike traditional approaches that rely on multiple fringe patterns, using only one or two patterns makes phase recovery and unwrapping difficult. To address this issue, a recurrent classification neural network (RCNN) has been developed, transforming the phase recovery and unwrapping tasks into a unified phase classification task. First, a training dataset consisting of 1,200 groups of data was collected to generate a total of 38,400 training samples, enabling the RCNN to learn the mapping between the input fringe patterns and the corresponding label maps. Then, based on the well-trained network, a label map is generated based on the input two fringe patterns using the output classification results. Finally, 3D reconstruction data could be obtained by combining the inferred label map with the vision system's parameters. A series of comprehensive experiments have been conducted to validate the performance of the proposed method.

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Gamma estimation method based on phase error coefficients vector in digital fringe projection system

Cited by 2 publications

References 21 publications

Three-dimensional measurement based on equal spacing binary fringe coding

Three-dimensional measurement based on equal spacing binary fringe coding

Robust structured light 3D imaging with two fringe patterns using recurrent classification neural network

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