Modeling the measurement precision of Fringe Projection Profilometry

Shenzhen Lv; Qian Kemao

doi:10.1038/s41377-023-01294-0

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Modeling the measurement precision of Fringe Projection Profilometry

Original Articles

- Modeling the measurement precision of Fringe Projection Profilometry
- Modeling the measurement precision of Fringe Projection Profilometry
- LSA 2023年12卷第11期页码：2480-2497
- Affiliations：
  
  School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
- Author bio：
  
  Qian Kemao (mkmqian@ntu.edu.sg)
- Funds：
- DOI：10.1038/s41377-023-01294-0
  中图分类号：
- 纸质出版日期：2023-11-30，
  
  网络出版日期：2023-10-30，
  
  收稿日期：2023-04-08，
  
  修回日期：2023-09-19，
  
  录用日期：2023-09-22
- Accepted：
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Modeling the measurement precision of Fringe Projection Profilometry[J]. LSA, 2023,12(11):2480-2497.

Lv, S. Z. & Kemao, Q. Modeling the measurement precision of Fringe Projection Profilometry. Light: Science & Applications, 12, 2480-2497 (2023).
Modeling the measurement precision of Fringe Projection Profilometry[J]. LSA, 2023,12(11):2480-2497. DOI： 10.1038/s41377-023-01294-0.

Lv, S. Z. & Kemao, Q. Modeling the measurement precision of Fringe Projection Profilometry. Light: Science & Applications, 12, 2480-2497 (2023). DOI： 10.1038/s41377-023-01294-0.

摘要

Abstract

Three-dimensional (3D) surface geometry provides elemental information in various sciences and precision engineering. Fringe Projection Profilometry (FPP) is one of the most powerful non-contact (thus non-destructive) and non-interferometric (thus less restrictive) 3D measurement techniques

featuring at its high precision. However

the measurement precision of FPP is currently evaluated experimentally

lacking a complete theoretical model for guidance. We propose the first complete FPP precision model chain including four stage models (camera intensity

fringe intensity

phase and 3D geometry) and two transfer models (from fringe intensity to phase and from phase to 3D geometry). The most significant contributions include the adoption of a non-Gaussian camera noise model

which

for the first time

establishes the connection between camera's electronics parameters (known in advance from the camera manufacturer) and the phase precision

and the formulation of the phase to geometry transfer

which makes the precision of the measured geometry representable in an explicit and concise form. As a result

we not only establish the full precision model of the 3D geometry to characterize the performance of an FPP system that has already been set up

but also explore the expression of the highest possible precision limit to guide the error distribution of an FPP system that is yet to build. Our theoretical models make FPP a more designable technique to meet the challenges from various measurement demands concerning different object sizes from macro to micro and requiring different measurement precisions from a few millimeters to a few micrometers.

关键词

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references

Fernandes, D. et al. Point-cloud based 3D object detection and classification methods for self-driving applications: a survey and taxonomy.Inf. Fusion68, 161–191 (2021)..

Dionisio, J. D. N., Burns III, W. G.&Gilbert, R. 3D Virtual worlds and the metaverse: current status and future possibilities.ACM Comput. Surv.45, 34 (2013)..

Jiang, Y. S., Karpf, S.&Jalali, B. Time-stretch LiDAR as a spectrally scanned time-of-flight ranging camera.Nat. Photonics14, 14–18 (2020)..

Lazaros, N., Sirakoulis, G. C.&Gasteratos, A. Review of stereo vision algorithms: from software to hardware.Int. J. Optomechatronics2, 435–462 (2008)..

Li, L. Time-of-Flight Camera—an Introduction. (Texas Instruments, 2014).

Zhu, F. P. et al. Accurate 3D measurement system and calibration for speckle projection method.Opt. Lasers Eng.48, 1132–1139 (2010)..

Gorthi, S. S.&Rastogi, P. Fringe projection techniques: whither we are?Opt. Lasers Eng.48, 133–140 (2010)..

Liu, Y. et al. In-situ areal inspection of powder bed for electron beam fusion system based on fringe projection profilometry.Addit. Manuf.31, 100940 (2020)..

Du, H. et al. Development and verification of a novel robot-integrated fringe projection 3D scanning system for large-scale metrology.Sensors17, 2886 (2017)..

Heist, S. et al. 5D hyperspectral imaging: fast and accurate measurement of surface shape and spectral characteristics using structured light.Opt. Express26, 23366–23379 (2018)..

Zhao, Y. Y. et al. Shortwave-infrared meso-patterned imaging enables label-free mapping of tissue water and lipid content.Nat. Commun.11, 5355 (2020)..

Liao, Y. H. et al. Portable high-resolution automated 3D imaging for footwear and tire impression capture.J. Forensic Sci.66, 112–128 (2021)..

Zhang, S. High-speed 3D imaging with digital fringe projection techniques. Proceedings of SPIE 11813, Tribute to James C. Wyant: The Extraordinaire in Optical Metrology and Optics Education. San Diego, CA, USA: SPIE, 2021, 118130 V.

Zhang, S.&Huang, P. S. Novel method for structured light system calibration.Opt. Eng.45, 083601 (2006)..

Tao, T. Y. et al. High-precision real-time 3D shape measurement based on a quad-camera system.J. Opt.20, 014009 (2018)..

Wang, Z. Y. et al. Single-shot 3D shape measurement of discontinuous objects based on a coaxial fringe projection system.Appl. Opt.58, A169–A178 (2019)..

Lv, S. Z. et al. Fringe projection profilometry method with high efficiency, precision, and convenience: theoretical analysis and development.Opt. Express30, 33515–33537 (2022)..

Wang, Z. Y., Nguyen, D. A.&Barnes, J. C. Some practical considerations in fringe projection profilometry.Opt. Lasers Eng.48, 218–225 (2010)..

Zhang, Z. H. et al. A simple, flexible and automatic 3D calibration method for a phase calculation-based fringe projection imaging system.Opt. Express21, 12218–12227 (2013)..

Zhang, S. Flexible and high-accuracy method for uni-directional structured light system calibration.Opt. Lasers Eng.143, 106637 (2021)..

Zhang, G. Y. et al. Correcting projector lens distortion in real time with a scale-offset model for structured light illumination.Opt. Express30, 24507–24522 (2022)..

Zhang, S. Comparative study on passive and active projector nonlinear gamma calibration.Appl. Opt.54, 3834–3841 (2015)..

Zhang, S. Rapid and automatic optimal exposure control for digital fringe projection technique.Opt. Lasers Eng.128, 106029 (2020)..

Wang, Y. J.&Zhang, S. Optimal fringe angle selection for digital fringe projection technique.Appl. Opt.52, 7094–7098 (2013)..

Li, J. L., Hassebrook, L. G.&Guan, C. Optimized two-frequency phase-measuring-profilometry light-sensor temporal-noise sensitivity.J. Opt. Soc. Am. A20, 106–115 (2003)..

Zuo, C. et al. Temporal phase unwrapping algorithms for fringe projection profilometry: a comparative review.Opt. Lasers Eng.85, 84–103 (2016)..

He, X. Y.&Kemao, Q. A comparative study on temporal phase unwrapping methods in high-speed fringe projection profilometry.Opt. Lasers Eng.142, 106613 (2021)..

Lyu, N. et al. Structured light-based underwater 3-D reconstruction techniques: a comparative study.Opt. Lasers Eng.161, 107344 (2023)..

Zheng, D. L. et al. Phase error analysis and compensation for phase shifting profilometry with projector defocusing.Appl. Opt.55, 5721–5728 (2016)..

Wang, H. X., Kemao, Q.&Soon, S. H. Valid point detection in fringe projection profilometry.Opt. Express23, 7535–7549 (2015)..

Wu, Z. J., Guo, W. B.&Zhang, Q. C. Two-frequency phase-shifting method vs. Gray-coded-based method in dynamic fringe projection profilometry: a comparative review.Opt. Lasers Eng.153, 106995 (2022)..

Rathjen, C. Statistical properties of phase-shift algorithms.J. Optical Soc. Am. A12, 1997–2008 (1995)..

EMVA. EMVA 1288 release 4.0 (2021). athttps://www.emva.org/standards-technology/emva-1288/emva-standard-1288-downloads-2/https://www.emva.org/standards-technology/emva-1288/emva-standard-1288-downloads-2/URL.

Hu, Y. et al. Online fringe pitch selection for defocusing a binary square pattern projection phase-shifting method.Opt. Express28, 30710–30725 (2020)..

Wei, Y. H., Liu, C. H.&Zhao, H. J. 3-D error estimation based on binocular stereo vision using fringe projection. 2017 2nd International Conference on Electrical and Electronics: Techniques and Applications. Beijing, China: EETA, (2017), 351-356.

de Groot, P. Principles of interference microscopy for the measurement of surface topography.Adv. Opt. Photonics7, 1–65 (2015)..

Häusler, G.&Willomitzer, F. Reflections about the holographic and non-holographic acquisition of surface topography: where are the limits?Light. : Adv. Manuf.3, 5 (2022)..

Situ, G. Deep holography.Light Adv. Manuf.3, 8 (2022)..

Huang, L. et al. Review of phase measuring deflectometry.Opt. Lasers Eng.107, 247–257 (2018)..

Xu, Y. J., Gao, F.&Jiang, X. Q. A brief review of the technological advancements of phase measuring deflectometry.PhotoniX1, 14 (2020)..

Zhang, S. Absolute phase retrieval methods for digital fringe projection profilometry: a review.Opt. Lasers Eng.107, 28–37 (2018)..

Jähne, B. Digital Image Processing. 6th edn. (Berlin: Spring, 2005).

FLIR. Machine vision sensor review (2023). athttps://www.flir.asia/landing/iis/machine-vision-camera-sensor-review/https://www.flir.asia/landing/iis/machine-vision-camera-sensor-review/.

Integrating Sphere. athttps://en.wikipedia.org/wiki/Integrating_sphere/https://en.wikipedia.org/wiki/Integrating_sphere/.

Walpole, R. E. et al. Probability&Statistics for Engineers&Scientists. 8th edn. (Upper Saddle River: Pearson Prentice Hall, 2007), 224.

The testing results: obtained from Daheng through personal request. athttps://www.daheng-imaging.com/product/area-scan-cameras/daheng/mer2-u3/https://www.daheng-imaging.com/product/area-scan-cameras/daheng/mer2-u3/.

Phong, B. T. Illumination for computer generated pictures.Commun. ACM18, 311–317 (1975)..

Texas Instruments. TI DLP® LightCrafter™ 4500 evaluation module user's guide (2017). athttps://www.ti.com/lit/ug/dlpu011f/dlpu011f.pdfhttps://www.ti.com/lit/ug/dlpu011f/dlpu011f.pdf.

Zhang, Z. H., Towers, C. E.&Towers, D. P. Time efficient color fringe projection system for 3D shape and color using optimum 3-frequency Selection.Opt. Express14, 6444–6455 (2006)..

Boreman, G. D. Modulation Transfer Function in Optical and Electro-Optical Systems. (Bellingham: SPIE, 2001).

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