DOI : https://doi.org/10.18517/ijaseit.12.5.14242

Adaptive Phase Error Suppression Concerning 3D surface Deformation Measurement on Color Digital Fringe Projection Profilometry

- Suprijanto (1), Naila Zahra (2), Vebi nadhira (3), Endang Juliastuti (4)
(1) Optics and Image Analysis Laboratory, Instrumentation and Control Research Group, Faculty of Industrial Technology, Institut Teknologi Bandung, Ganesha 10 Bandung, Indonesia
(2) Optics and Image Analysis Laboratory, Instrumentation and Control Research Group, Faculty of Industrial Technology, Institut Teknologi Bandung, Ganesha 10 Bandung, Indonesia
(3) Optics and Image Analysis Laboratory, Instrumentation and Control Research Group, Faculty of Industrial Technology, Institut Teknologi Bandung, Ganesha 10 Bandung, Indonesia
(4) Optics and Image Analysis Laboratory, Instrumentation and Control Research Group, Faculty of Industrial Technology, Institut Teknologi Bandung, Ganesha 10 Bandung, Indonesia
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How to cite (IJASEIT) :
Suprijanto, -, et al. “Adaptive Phase Error Suppression Concerning 3D Surface Deformation Measurement on Color Digital Fringe Projection Profilometry”. International Journal on Advanced Science, Engineering and Information Technology, vol. 12, no. 5, Oct. 2022, pp. 1973-80, doi:10.18517/ijaseit.12.5.14242.
Citation Format :
3D surface measurement based on phase-shifting profilometry (PSP) has been actively developed in recent years. Three color channels of RGB that are modulated to generate a one-shot PSP method is a concept of color digital fringe pattern profilometry (CDFPP). The CDFPP is a promising technique for the 3D imaging profile of dynamic surface deformation if several phase errors in the one-shot PSP method can be suppressed. This work proposes a processing scheme for phase error suppression schemes (PESS) based on retrieving the modulated sinusoidal fringe and color fringe normalization in PSP using RGB color channel. The processing of PESS consists of tunable bandpass filtering (BPF) followed by fringe normalization. The initial BPF function is defined based on a smoothing spline data set of frequency and power spectrum from the baseline color fringe image. The predefine BPF function could be tunable during the imaging process by considering each frame's condition and RGB channel spectrum mapping. The corrected fringe images are then normalized from the color imbalance, and the phase shift is calculated using the conventional three-step PSP. For evaluation, PESS is performed to reconstruct simulator membrane deformation from four different static profiles and tested to observe the 3D surface of continuous membrane deformation. The PESS could suppress the phase errors of less than 30% less absolute errors than the conventional method and successfully reconstruct the 3D surface for low-frequency continuous membrane deformation with minimizing phase errors.

S. Zhang, “Recent progresses on real-time 3D shape measurement using digital fringe projection techniques,” Optics and Lasers in Engineering, vol. 48, no. 2, pp. 149-158, Feb. 2010, doi: 10.1016/j.optlaseng.2009.03.008.

J. Xu and S. Zhang, “Status, challenges, and future perspectives of fringe projection profilometry,” Optics and Lasers in Engineering. Elsevier Ltd, p. 106193, Jun. 04, 2020, doi: 10.1016/j.optlaseng.2020.106193.

B. Li, Y. An, and S. Zhang, “Single-shot absolute 3D shape measurement with Fourier transform profilometry,” Applied Optics, vol. 55, no. 19, p. 5219, 2016, doi: 10.1364/AO.55.005219.

M. Takeda, H. Ina, and S. Kobayashi, “Fourier-Transform Method of Fringe-Pattern Analysis for Computer-Based Topography and Inteferometry.,” Journal of the Optical Society of America, vol. 72, no. 1, pp. 156-160, 1982, doi: 10.1364/JOSA.72.000156.

M. Padilla, M. Servin, and G. Garnica, “Fourier analysis of RGB fringe-projection profilometry and robust phase-demodulation methods against crosstalk distortion,” Optics Express, vol. 24, no. 14, p. 15417, 2016, doi: 10.1364/oe.24.015417.

B. Li, Z. Liu, and S. Zhang, “Motion-induced error reduction by combining Fourier transform profilometry with phase-shifting profilometry,” Optics Express, vol. 24, no. 20, p. 23289, 2016, doi: 10.1364/oe.24.023289.

F. Lí¼, S. Xing, and H. Guo, “Self-correction of projector nonlinearity in phase-shifting fringe projection profilometry,” Applied Optics, vol. 56, no. 25, p. 7204, 2017, doi: 10.1364/AO.56.007204.

L. Zhu, Y. Cao, D. He, and C. Chen, “Grayscale imbalance correction in real-time phase measuring profilometry,” Optics Communications, vol. 376, pp. 72-80, 2016, doi: 10.1016/j.optcom.2016.05.013.

M. Padilla, M. Servin, and G. Garnica, “Profilometry with digital fringe-projection at the spatial and temporal Nyquist frequencies,” Opt. Express, vol. 25, no. 19, pp. 22292-22302, 2017, doi: 10.1364/OE.25.022292.

S. Xing and H. Guo, “Directly recognizing and removing the projector nonlinearity errors from a phase map in phase-shifting fringe projection profilometry,” Optics Communications, vol. 435, pp. 212-220, Mar. 2019, doi: 10.1016/j.optcom.2018.11.045.

C. Jiang, S. Xing, and H. Guo, “Fringe harmonics elimination in multi-frequency phase-shifting fringe projection profilometry,” Optics Express, vol. 28, no. 3, p. 2838, 2020, doi: 10.1364/oe.384155.

C. Y. Liu and C. Y. Wang, “Investigation of Phase Pattern Modulation for Digital Fringe Projection Profilometry,” Measurement Science Review, vol. 20, no. 1, pp. 43-49, 2020, doi: 10.2478/msr-2020-0006.

M. Duan, Y. Jin, C. Xu, X. Xu, C. Zhu, and E. Chen, “Phase-shifting profilometry for the robust 3-D shape measurement of moving objects,” Optics Express, vol. 27, no. 16, p. 22100, Aug. 2019, doi: 10.1364/oe.27.022100.

Z. Liu, P. C. Zibley, and S. Zhang, “Motion-induced error compensation for phase shifting profilometry,” Optics Express, vol. 26, no. 10, p. 12632, 2018, doi: 10.1364/oe.26.012632.

X. Liu, T. Tao, Y. Wan, and J. Kofman, “Real-time motion-induced-error compensation in 3D surface-shape measurement,” Optics Express, vol. 27, no. 18, p. 25265, 2019, doi: 10.1364/oe.27.025265.

J. Qian, T. Tao, S. Feng, Q. Chen, and C. Zuo, “Motion-artifact-free dynamic 3D shape measurement with hybrid Fourier-transform phase-shifting profilometry,” Optics Express, vol. 27, no. 3, p. 2713, Feb. 2019, doi: 10.1364/OE.27.002713.

W.-H. Su, “Color-encoded fringe projection for 3D shape measurements,” Optics Express, vol. 15, no. 20, p. 13167, Oct. 2007, doi: 10.1364/oe.15.013167.

J. Pan, P. S. Huang, and F.-P. Chiang, “Color-encoded digital fringe projection technique for high-speed 3D shape measurement: color coupling and imbalance compensation,” Two- and Three-Dimensional Vision Systems for Inspection, Control, and Metrology, vol. 5265, no. 1, pp. 205-212, 2004, doi: 10.1117/12.527760.

Y. Hu, J. Xi, J. Chicharo, and Z. Yang, “Blind color isolation for color-channel-based fringe pattern profilometry using digital projection,” Journal of the Optical Society of America A, vol. 24, no. 8, p. 2372, Aug. 2007, doi: 10.1364/josaa.24.002372.

L. Rao and F. Da, “Neural network based color decoupling technique for color fringe profilometry,” Optics and Laser Technology, vol. 70, pp. 17-25, 2015, doi: 10.1016/j.optlastec.2015.01.007.

W. Li and S. Duan, “Color calibration and correction applying linear interpolation technique for color fringe projection system,” Optik, vol. 127, no. 4, pp. 2074-2082, 2016, doi: 10.1016/j.ijleo.2015.11.093.

M. J. Baker, J. Xi, and J. F. Chicharo, “Neural network digital fringe calibration technique for structured light profilometers,” Applied Optics, vol. 46, no. 8, p. 1233, Mar. 2007, doi: 10.1364/AO.46.001233.

M. Ma, Y. Cao, D. He, C. Chen, and Y. Wan, “Grayscale imbalance correcting method based on fringe normalization in RGB tricolor real-time three-dimensional measurement,” Optical Engineering, vol. 55, no. 3, p. 034102, 2016, doi: 10.1117/1.OE.55.3.034102.

T. T. Chung, T. W. Liu, M. H. Shih, and Y. T. Tu, “Design of color fringe projection sequences for 3D shape measurements,” 2010 Symposium on Photonics and Optoelectronic, SOPO 2010 - Proceedings, pp. 1-4, 2010, doi: 10.1109/SOPO.2010.5504210.

J. L. Flores, A. Muñoz, S. Ordoñes, G. Garcia-Torales, and J. A. Ferrari, “Color-fringe pattern profilometry using an efficient iterative algorithm,” Optics Communications, vol. 391, no. December 2016, pp. 88-93, 2017, doi: 10.1016/j.optcom.2016.12.058.

C. Jiang et al., “Multi-frequency color-marked fringe projection profilometry for fast 3D shape measurement of complex objects,” Optics Express, vol. 23, no. 19, p. 24152, 2015, doi: 10.1364/oe.23.024152.

S. Ma, R. Zhu, C. Quan, B. Li, C. J. Tay, and L. Chen, “Blind phase error suppression for color-encoded digital fringe projection profilometry,” Optics Communications, vol. 285, no. 7, pp. 1662-1668, Apr. 2012, doi: 10.1016/j.optcom.2011.12.027.

K. G. Larkin, D. J. Bone, and M. A. Oldfield, “Natural demodulation of two-dimensional fringe patterns II Stationary phase analysis of the spiral phase quadrature transform,” Journal of the Optical Society of America A, vol. 18, no. 8, p. 1871, 2001, doi: 10.1364/josaa.18.001871.

J. A. Quiroga and M. Servin, “Isotropic n-dimensional fringe pattern normalization,” Optics Communications, vol. 224, no. 4-6, pp. 221-227, Sep. 2003, doi: 10.1016/j.optcom.2003.07.014.

Y. Wang, L. Liu, J. Wu, X. Chen, and Y. Wang, “Hilbert transform-based crosstalk compensation for color fringe projection profilometry,” Optics Letters, vol. 45, no. 8, p. 2199, Apr. 2020, doi: 10.1364/ol.392061.

C. Quan, C. J. Tay, and L. J. Chen, “A study on carrier-removal techniques in fringe projection profilometry,” Optics and Laser Technology, vol. 39, no. 6, pp. 1155-1161, Sep. 2007, doi: 10.1016/j.optlastec.2006.09.003.

L. Xu and J. Zhou, “A model-averaging approach for smoothing spline regression,” Communications in Statistics: Simulation and Computation, vol. 48, no. 8, pp. 2438-2451, 2019, doi: 10.1080/03610918.2018.1457694.

D. S. G. Pollock, “Smoothing with Cubic Splines,” in A Handbook of Time Series Analysis, Signal Processing, and Dynamics, London: Academic Press, 1999, p. 293.

P. Cerejeiras and U. Kí¤hler, “Monogenic Signal Theory,” in Operator Theory, Springer Basel, 2014, pp. 1-22.

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