Point-to-point compensation method for color coupling and imbalance in color-fringe pattern profilometry

Wu, Mingyang; Wu, Guofang; Zhang, Shengming; Wu, Yanxue; Liu, Fei; Fan, Naiji

doi:10.1088/2040-8986/aba3b5

Cited by 4 publications

(4 citation statements)

References 41 publications

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“…Compared with Ref. [16], the proposed method did not need any extra images to obtain more distorted information for correction. Although the proposed method possesses the aforementioned advantages, it has its own limitations.…”

Section: Discussionmentioning

confidence: 99%

“…Wan et al [15] proposed an active phase error suppression method for color phase-shifting fringe projection based on hue precorrection. Wu et al [16] presented a point-to-point method based on the correspondence between camera pixels and projector pixels to accomplish the compensation of the full field. However, those methods require extra images with prior knowledge to calculate the compensation factors, which means that once the measuring condition changes, the calibration process is repeated.…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear Error Correction for Color Phase-Shifting Profilometry with Histogram Equalization

et al. 2022

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Because color patterns with multiple channels can carry more information than gray patterns with only one channel, color phase-shifting profilometry (CPSP) has been widely used for high-speed, three-dimensional (3D) shape measurement. However, the accuracy of CPSP suffers from nonlinear errors caused by color crosstalk. This paper presents an effective nonlinear error correction method for CPSP based on histogram equalization. The two main steps of the proposed method are eliminating nonlinear errors with histogram equalization and optimizing the results using a spline fitting algorithm. Compared with other compensation methods, the proposed approach does not require any precalibration information or additional patterns, which are very time-consuming. The simulations and experiments indicate that the proposed method has a promising performance for nonlinear error elimination.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nonlinear Error Correction for Color Phase-Shifting Profilometry with Histogram Equalization

et al. 2022

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“…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]. The temporal phase unwrapping performs the unwrapping process pixel by pixel and therefore has advantage of high robustness.…”

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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“…Ma et al [27] proposed a blind phase error suppression approach based on isotropic n-dimensional fringe pattern normalization [28] and carrier squeezing interferometry [29]. Wu et al [30] proposed a point-to-point compensation method for color coupling and imbalance. The proposed method achieves point-topoint compensation based on the correspondence between camera pixels and projector pixels.…”

Section: Introductionmentioning

confidence: 99%

Blind Crosstalk Correction for Color Fringe Projection Profilometry Combining the Sine and Cosine Phase-Shifting Patterns

Yang

Zhang

et al. 2022

Journal of Sensors

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Color crosstalk is challenging for color fringe projection profilometry, which will cause color imbalance and phase-shift deviation, thus resulting in phase error. To address this challenge, this paper presents a blind crosstalk correction method for color phase-shifting fringe projection profilometry without crosstalk calibration. Three channels of the color fringe are firstly normalized to resolve color imbalance. The phase error induced by phase-shift deviation between three channels doubles the frequency of the color fringe. Therefore, the original cosine color fringe is shifted by quarter period to generate another sine color fringe to compensate the periodic phase error. Both simulations and experiments were carried out, and their results confirmed the effectiveness and accuracy of the proposed method.

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Point-to-point compensation method for color coupling and imbalance in color-fringe pattern profilometry

Cited by 4 publications

References 41 publications

Nonlinear Error Correction for Color Phase-Shifting Profilometry with Histogram Equalization

Nonlinear Error Correction for Color Phase-Shifting Profilometry with Histogram Equalization

Measurement depth modeling and extension for geometric constraint phase unwrapping method

Blind Crosstalk Correction for Color Fringe Projection Profilometry Combining the Sine and Cosine Phase-Shifting Patterns

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