High speed fringe projection for dynamic shape measurement using binary phase mask. Part 1: theory and simulation

Guo, Wen; Huntley, Jonathan M.; Coggrave, C. R.; Ruiz, Pablo D.

doi:10.1016/j.optlaseng.2022.107021

Cited by 5 publications

(1 citation statement)

References 37 publications

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“…The three-dimensional shape of an object is one of its important features. There are many methods for threedimensional shape reconstruction of complex surface shapes [1][2][3][4][5][6][7]. The traditional methods, such as Fourier transform profilometry (FTP) [1,2] and phase measurement profilometry (PMP) [3,4], which have been widely used in many fields, such as industrial detection, biomedicine and physical profiling, because these methods are non-contact measurement based on structural light projection and have high accuracy [8].…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional shape measurement based on deep learning

Zheng,

Dai

2023

Fourteenth International Conference on Information Optics and Photonics (CIOP 2023)

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Section: Introductionmentioning

confidence: 99%

Three-dimensional shape measurement based on deep learning

Zheng,

Dai

2023

Fourteenth International Conference on Information Optics and Photonics (CIOP 2023)

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Recent Progress of Full-Field Three-Dimensional Shape Measurement Based on Phase Information

Bai,

Zhang,

et al. 2024

Nanomanuf Metrol

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Full-field three-dimensional (3D) measurement technology based on phase information has become an indispensable part of geometric dimension measurement in modern scientific research and engineering applications. This field has been developing and evolving for the study of highly reflective phenomena, diffuse reflections, and specular surfaces, and many novel methods have emerged to increase the speed of measurements, enhance data accuracy, and broaden the robustness of the system. Herein, we will discuss the latest research progress in full-field 3D shape measurement based on phase information systematically and comprehensively. First, the fundamentals of 3D shape measurement based on phase information are introduced, namely, phase-shifting and transform-based methods. Second, recent technological innovations are highlighted, including increases in measurement speed and automation and improvements in robustness in complex environments. In particular, the challenges faced by these technological advances in solving highly dynamic, composite surface measurement problems are presented, i.e., with multiexposure techniques proposed for high dynamics that extend the dynamic range of the camera to reduce the effects of overexposure but increase the cost of time and have high hardware requirements, fringe adaptive techniques that overcome light variations but are computationally complex, and multipolarized camera techniques that reduce the effects of light variations but are sensitive to the light source. Third, the phase-shifting method combined with coding is proposed to improve the measurement speed, but the accuracy is slightly reduced. Deep learning techniques are proposed to cope with measurements in complex environments, but the dataset computation process is cumbersome. Finally, future research directions are suggested, and the challenges are presented. Overall, this work provides a reference for researchers and engineers.

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