A novel phase-shifting profilometry to realize temporal phase unwrapping simultaneously with the least fringe patterns

Wu, Haitao; Cao, Yiping; An, Haihua; Li, Yang; Li, Hongmei; Xu, Chuan; Yang, Na

doi:10.1016/j.optlaseng.2022.107004

Cited by 25 publications

(7 citation statements)

References 31 publications

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“…Phase shifting profilometry 23 projects N(N ≥ 3) sinusoidal stripe patterns with equal phase shifts within one cycle onto the surface of the measured object, and the camera captures the deformed fringes to accurately solve the phase information modulated by the height of the measured object's surface. The five-step phase-shifting algorithm is used in this paper, and the captured images are represented as E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 1 ; 1 1 7 ; 4 1 2…”

Section: Phase Shifting Profilometrymentioning

confidence: 99%

“…Phase shifting profilometry 23 projects N(N≥3) sinusoidal stripe patterns with equal phase shifts within one cycle onto the surface of the measured object, and the camera captures the deformed fringes to accurately solve the phase information modulated by the height of the measured object’s surface. The five-step phase-shifting algorithm is used in this paper, and the captured images are represented as In(u,v)=A(u,v)+B(u,v)cos[φ(u,v)+δn],δn=2π·(n−1)N(n≤N),where A(u,v) is the background light intensity, B(u,v) is the modulation, φ(u,v) is the phase modulated by the height information of the object, and δn is the phase shift amount.…”

Section: Principlementioning

confidence: 99%

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Three-dimensional reconstruction based on binocular structured light with an error point filtering strategy

Li,

Yang,

Wan

et al. 2024

Opt. Eng.

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Gray code assisted phase shifting technology can achieve robust and noise-tolerated three-dimensional (3D) shape measurements. To solve the issues of unsynchronized brightness changes, local overexposure, and edge coding errors caused by inconsistent reflectivity of the surface in complex industrial scenes, as well as defocusing caused by noncontinuous surfaces and varying distances, we combine the advantages of a large imaging range in passive stereo vision and high precision in active structured light imaging. It uses a consumer-grade projector to project gray code and stripe patterns, whereas two precalibrated color industrial cameras capture raw images and obtain the original channel data. Gray code and reverse gray code images are projected to solve the problems of binarization and boundary blur. In addition, an error point filtering strategy is proposed to retain pixels with decoding errors of less than two bits. The use of softargmin for subpixel matching of absolute phase results in a high precision disparity map. We present a simple and high precision 3D measurement system for industrial objects. Experiments on 3D measurements in complex industrial scenes showed that the proposed method can achieve high precision and robust 3D shape measurements.

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Section: Phase Shifting Profilometrymentioning

confidence: 99%

“…Phase shifting profilometry 23 projects N(N≥3) sinusoidal stripe patterns with equal phase shifts within one cycle onto the surface of the measured object, and the camera captures the deformed fringes to accurately solve the phase information modulated by the height of the measured object’s surface. The five-step phase-shifting algorithm is used in this paper, and the captured images are represented as In(u,v)=A(u,v)+B(u,v)cos[φ(u,v)+δn],δn=2π·(n−1)N(n≤N),where A(u,v) is the background light intensity, B(u,v) is the modulation, φ(u,v) is the phase modulated by the height information of the object, and δn is the phase shift amount.…”

Section: Principlementioning

confidence: 99%

Three-dimensional reconstruction based on binocular structured light with an error point filtering strategy

Li,

Yang,

Wan

et al. 2024

Opt. Eng.

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“…where g ′ and g ′′ represents the background and modulation intensity. ϕ is the wrapped phase to be solved for, which can be extracted by the following equation [30][31][32][33][34].…”

Section: Wrapped Phase Extraction Based On Pspmentioning

confidence: 99%

An efficient high dynamic range 3D shape reconstruction method based on double phase-shifting profilometry

Wang,

Yang

2023

Meas. Sci. Technol.

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Phase-shifting profilometry (PSP) is the most widely used wrapped phase extraction method due to the advantages of high accuracy and resolution, robust to noise. However, due to the local specular reflection of the measured surfaces and the limited camera dynamic range, some pixels of the captured fringes become intensity saturated, thus introducing wrapped phase error. In this work, we simulate the Fourier spectrum of the saturated fringe and represent the saturated fringe approximately by a third-order Fourier series. Subsequently, we establish the saturation-induced wrapped phase error model. According to this model, it can be found that for the N-step phase-shifting method, the spatial frequency of the saturation-induced wrapped phase error is N times of that of the ideal wrapped phase. We phase shift the N-step phase-shifting fringe sequence π/N to generate the additional phase-shifting fringe sequence, and thus generate the opposite saturation-induced wrapped phase error. Finally, the saturation-induced wrapped phase error can be greatly reduced by fusing the wrapped phases of the two sets of phase-shifting fringe sequences. Compared with the traditional method and the adaptive projection fringe method, the phase error of the double N-step phase-shifting method is reduced by 69.92% and 65.2%, respectively.

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“…The essence of phase unwrapping is to find the fringe order ( ) , k xy . Many methods for phase unwrapping have been proposed, which most of them can be categorized into two types: the temporal and the spatial phase unwrapping [7]. The former method aims to collect more information for phase unwrapping from temporal axis, e.g., the multi-frequency heterodyne [8], multi-frequency phase-shifting technology [9], gray-code method [10] and phase-shift-code method [11,12].…”

Section: Introductionmentioning

confidence: 99%

Measurement depth modeling and extension for geometric constraint phase unwrapping method

2024

International Conference on Optical and Photonic Engineering (icOPEN 2023)

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As an important phase unwrapping method in Fringe Projecting Profilometry, the geometric constraint enables pixel-by-pixel computation while avoiding the projection of additional patterns. However, its measurement depth is limited to one fringe period and influenced by multiple factors from the camera-projector system. There is still a lack of a generalized model that can describe the measurement depth. In this paper, to completely understand the variables related to the measurement depth, we analyze the unwrapping process of geometric constraint and derive a generalized model. To validate the key variables in the model, we establish a virtual camera-projector system and conduct simulations. Based on the simulation results, we propose four ways to extend the measurement depth, including (a) selecting a reference plane farther away from the camera, (b) designing the fringe patterns with fewer periods, (c) using the shorter focal lens and (d) reducing the camera-projector distance.

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A novel phase-shifting profilometry to realize temporal phase unwrapping simultaneously with the least fringe patterns

Cited by 25 publications

References 31 publications

Three-dimensional reconstruction based on binocular structured light with an error point filtering strategy

Three-dimensional reconstruction based on binocular structured light with an error point filtering strategy

An efficient high dynamic range 3D shape reconstruction method based on double phase-shifting profilometry

Measurement depth modeling and extension for geometric constraint phase unwrapping method

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