Robust geometric, phase and colour structured light projection system calibration

• Autorzy: Szelag K. , Maczkowski G. , Gierwialo R. , Gebarska A. , Sitnik R.

Identyfikatory

DOI

10.1016/j.opelre.2017.10.001

• Języki publikacji: EN

Abstrakty

EN

This paper introduces a new comprehensive procedure for both geometric and colour calibration of structured light system. In order to perform both geometric and colour calibration procedure, a new calibration artifact is proposed. The intrinsic and extrinsic parameters of projector and camera are estimated by using an extended pinhole camera model with a tangential and radial distortion. Camera image plane coordinates are obtained by extracting features from images of a calibration artifact. Projector image plane coordinates are calculated on the basis of continuous phase maps obtained from a fringe pattern phase reconstruction procedure. In order to stereo calibrate camera-projector system, pairs of corresponding image plane points are calculated with subpixel accuracy. In addition, one of three pattern views is used in colour calibration. RGB values of a colour field pattern detected by camera and their reference values are compared. This comparison leads to derivation of a colour transformation matrix. The performance of the proposed method is tested by measuring plane, sphere and distance reference. Also 360 degrees complex object 3D model from a set of measurements is obtained. Residual mean errors for all tests performed are calculated.

Słowa kluczowe

EN

structured light; colour calibration; geometric calibration; low cost scanner; simple calibration

• Wydawca: Stowarzyszenie Elektryków Polskich ; Polska Akademia Nauk ; Wojskowa Akademia Techniczna im. Jarosława Dąbrowskiego
• Czasopismo: Opto-Electronics Review
• Rocznik: 2017
• Tom: Vol. 25, No. 4
• Strony: 326--336
• Opis fizyczny: Bibliogr. 42 poz., il., rys., tab.

Twórcy

autor

Szelag K.

• Faculty of Mechatronics, Warsaw University of Technology, Warsaw, Poland

autor

Maczkowski G.

• Faculty of Mechatronics, Warsaw University of Technology, Warsaw, Poland

autor

Gierwialo R.

• Faculty of Mechatronics, Warsaw University of Technology, Warsaw, Poland

autor

Gebarska A.

• SMARTTECH Poland Warsaw, Poland

autor

Sitnik R.

• Faculty of Mechatronics, Warsaw University of Technology, Warsaw, Poland

Bibliografia

• [1] R. Labayrade, D. Aubert, J.-P. Tarel, Real time obstacle detection in stereovision on non flat road geometry through “v-disparity” representation, Intell. Veh. Symp. 2 (2002) 646–651.
• [2] M. Witkowski, R. Sitnik, M. Kujawiska, W. Rapp, M. Kowalski, B. Haex, S. Mooshake, 4d measurement system for automatic location of anatomical structures, Proc. SPIE 6191 (2006), 61910H–61910H–11.
• [3] C. Liguori, A. Paolillo, A. Pietrosanto, An on-line stereo-vision system for dimensional measurements of rubber extrusions, Measurement 35 (2004) 221–231.
• [4] J.J. Aguilar, M. Lope, F. Torres, A. Blesa, Development of a stereo vision system for non-contact railway concrete sleepers measurement based in holographic optical elements. Measurement, J. Int. Meas. Confederation 38 (2) (2005) 154–165.
• [5] J. Geng, Structured-light 3d surface imaging: a tutorial, Adv. Opt. Photonics 3 (2) (2011) 128–160.
• [6] J. Salvi, S. Fernandez, T. Pribanic, X. Llado, A state of the art in structured light patterns for surface profilometry, Pattern Recog. (Vol 43, 2010).
• [7] R. Sitnik, J. Woznicki, et al., Digital fringe projection system for large-volume 360-deg shape measurement, Opt. Eng. 41 (2) (2002) 443–449.
• [8] J. Schanda, Colorimetry: understanding the CIE system, John Wiley & Sons, 2007.
• [9] Z. Li, Accurate calibration method for a structured light system, Opt. Eng. 47 (5) (2008) 053604.
• [10] F. Chen, G.M. Brown, M. Song, Overview of three-dimensional shape measurement using optical methods, Opt. Eng. 39 (January (1)) (2000).
• [11] R. Sitnik, New method of structure light measurement system calibration based on adaptive and effective evaluation of 3d-phase distribution, Opt. Metrol. 5856 (2005) 109–117.
• [12] P. Hariharan, B.F. Oreb, T. Eiju, Digital phase-shifting interferometry: a simple error-compensating phase calculation algorithm, Appl. Opt. 26 (5) (1987) 2504–2506.
• [13] J.A. Quiroga, E. Bernabeu, Phase-unwrapping algorithm for noisy phase-map processing, Appl. Opt. 33 (29) (1994) 6725–6731.
• [14] S. Zhang, S.-T. Yau, High-resolution, real-time 3d absolute coordinate measurement based on a phase-shifting method, Opt. Express 14 (7) (2006) 2644–2649.
• [15] M. Axholt, Pinhole camera calibration in the presence of human noise, in: Doctoral thesis, LiU-Tryck, Linkoping, Sweden, 2011.
• [16] X. Mei, S. Yang, J. Rong, X. Ying, S. Huang, H. Zha, Radial lens distortion correction using cascaded oneparameter division model, Image Processing (ICIP) IEEE International Conference (2015) 3615–3619.
• [17] Y. Tang, Y. Li, J. Luo, Parametric distortion-adaptive neighborhood for omnidirectional camera, Appl. Opt. 54 (23) (2015) 6969–6978.
• [18] O.D. Faugeras, Three-dimensional computer vision: A geometric viewpoint, MIT Press, 1993.
• [19] Z. Zhang, A flexible new technique for camera calibration, IEEE Trans. Pattern Anal. Mach. Intell. 2000 (22) (2009) 1330–1334.
• [20] J.J. More, The levenberg-marquardt algorithm: Implementation and theory, Numer. Anal. 630 (1978) 105–116.
• [21] B.E. Bayer. Color imaging array. US patent 3971065, Issued 1976–07–20.
• [22] C. Mauer, D. Wueller, Measuring the spectral response with a set of interference filters, Proc. SPIE 7250 (2009), 72500S–72500S–10.
• [23] S. Lin, L. Zhang. Determining the radiometric response function from a single grayscale image, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05) 2005 2.
• [24] M.D. Grossberg, S.K. Nayar, Modeling the Space of Camera Response Functions, IEEE Trans. Pattern Anal. Mach. Intell. 26 (10) (2004) 1272–1282.
• [25] G. Wyszecki, W.S. Stiles, Color Science. Concepts and Methods, Quantitative Data and Formulae, John Wiley & Sons, 2000, pp. 117–173.
• [26] J.Y. Hardeberg, Acquisition and reproduction of color images: colorimetric and multispectral approaches, École Nationale Supérieure des Télécommunication, 2001, PhD thesis.
• [27] H. Anwar, I. Din, K. Park, Projector calibration for 3d scanning using virtual target images, Int. J. Precis. Eng. Manuf. 13 (1) (2012) 125–131.
• [28] J. Draréni, J. Roy, P. Sturm, Methods for geometrical video projector calibration Mach, Vision Appl. 23 (1) (2011) 79–89.
• [29] J.S. Wheat, S. Choppin, A. Goyal, Development, assessment of a microsoft kinect based system for imaging the breast in three dimensions, Med. Eng. Phys. 36 (6) (2014) 732–738.
• [30] D. Moreno, G. Taubin, 2012. Simple, accurate, and robust projector-camera calibration, 2nd International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), October, 464–471.
• [31] H. Saito, Y. Sato, K. Yamauchi, Calibration of a structured light system by observing planar object from unknown viewpoints, 19th International Conference on Pattern Recognition ICPR2008, Keio Univ., Yokohama, Japan, 2008.
• [32] J. Wilm, O.V. Olesen, R. Larsen, Accurate and simple calibration of dlp projector systems, Proc. SPIE 8979 (2014) 1–9.
• [33] J. Weng, P. Cohen, M. Herniou, Camera calibration with distortion models and accuracy evaluation, IEEE Trans. Pattern Anal. Mach. Intell. 10 (1992) 965–980.
• [34] R.I. Hartley, P. Sturm, Computer vision and image understanding, Triangulation 68 (2) (1997) 146–157.
• [35] J.F. Blinn, A homogeneous formulation for lines in 3 space, ACM SIGGRAPH Comput. Graphics 11 (1977) 237–241, ACM.
• [36] D. Pascale, RGB coordinates of the Macbeth ColorChecker, 2006. http://www.babelcolor.com/index.htm.files/RGB%20Coordinates%20of%20the%20Macbeth%20ColorChecker.pdf (Accessed: 25 March 2016).
• [37] IEC 61966–2-1:1999. Multimedia systems and equipment. Colour measurement and management. Colour management. Default RGB colour space: sRGB.
• [38] ISO 10360–2:2009 geometrical product specifications (gps) – acceptance and reverification tests for coordinate measuring machines (cmm) – part 2: Cmms used for measuring linear dimensions, 2009.
• [39] Vdi/vde 2617–6, accuracy of cmms – guideline for the application of iso 10360 to cmms with optical distance sensors, 1997.
• [40] R. Sitnik, M. Kujawinska, J. Woznicki, Digital fringe projection system for large-volume 360-deg shape measurement, Opt. Eng. 41 (2) (2002) 443–449.
• [41] K. Khoshelham, S.O. Elberink, Accuracy and resolution of kinect depth data for indoor mapping applications, Sensors 12 (2) (2012) 1437.
• [42] J. Zhu, L. Wang, R. Yang, J. Davis, Fusion of time-of-flight depth and stereo for high accuracy depth maps, in: Computer Vision and Pattern Recognition, CVPR 2008, June, 2008, pp. 1–8.