Еstimating the measurement error of the coordinates of markers on images recorded with a stereoscopic system

Gorevoy, A.V., Kolyuchkin, V.Y., Machikhin, A.S.

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Publication in Journal of Optical Technology

For Russian citation (Opticheskii Zhurnal):

Горевой А.В., Колючкин В.Я., Мачихин А.С. Оценка погрешности измерения координат маркеров на изображениях, регистрируемых стереоскопической системой// Оптический журнал. 2020. Т. 87. № 5. С. 18–30. http://doi.org/10.17586/1023-5086-2020-87-05-18-30

Gorevoĭ A.V., Kolyuchkin V.Ya., Machikhin A.S. Еstimating the measurement error of the coordinates of markers on images recorded with a stereoscopic system [in Russian] // Opticheskii Zhurnal. 2020. V. 87. № 5. P. 18–30. http://doi.org/10.17586/1023-5086-2020-87-05-18-30

For citation (Journal of Optical Technology):

A. Gorevoĭ, V. Kolyuchkin, and A. Machikhin, "Estimating the measurement error of the coordinates of markers on images recorded with a stereoscopic system," Journal of Optical Technology . 87(5), 266-275 (2020). https://doi.org/10.1364/JOT.87.000266

Abstract:

This paper proposes a method of estimating the error of measuring the coordinates of markers (corners of cells) on images recorded by a stereoscopic system. This problem needs to be solved in order to determine the error of the three-dimensional geometrical measurements made with such systems. At the design stage, the method is applied to segments of an image synthesized on the basis of the aberrational characteristics of the optical system. At the operating stage, the method is supplemented by an estimate of the parameters describing the noise on the recorded images. The efficiency of the proposed approach is confirmed by computer simulation and experiments. The results of this paper make it possible to connect the design of the optical system and the development of data-processing algorithms into a single procedure when stereoscopic measurement devices are being created, as well as to estimate the errors of three-dimensional geometrical measurements when these devices are being operated.

Keywords:

stereoscopic instruments, geometric measurement, calibration, image processing

OCIS codes: 120.0120, 330.1400, 230.0230

References:

1. T. Luhmann, S. Robson, S. Kyle, and J. Boehm, Close-Range Photogrammetry and 3D Imaging (De Gruyter, Berlin, 2013).

2. S. Zhou and S. Xiao, “3D face recognition: a survey,” Human-Centric Comput. Inf. Sci. 8, 35 (2018).

3. K. Schwab, R. Smith, V. Brown, M. Whyte, and I. Jourdan, “Evolution of stereoscopic imaging in surgery and recent advances,” World J. Gastrointest. Endosc. 9(8), 368–377 (2017).

4. J. Geng and J. Xie, “Review of 3-D endoscopic surface-imaging techniques,” IEEE Sens. J. 14(4), 945–960 (2014).

5. J. N. Mait, G. W. Euliss, and R. A. Athale, “Computational imaging,” Adv. Opt. Photon. 10(2), 409–483 (2018).

6. Z. Chen, K.-Y. K. Wong, Y. Matsushita, and X. Zhu, “Depth from refraction using a transparent medium with unknown pose and refractive index,” Int. J. Comput. Vis. 102(1–3), 3–17 (2013).

7. L. Wu, J. Zhu, H. Xie, and M. Zhou, “Single-lens 3D digital imagecorrelation system based on a bilateral telecentric lens and a bi-prism: systematic error analysis and correction,” Opt. Lasers Eng. 87, 129–138 (2016).

8. D. G. Stork and M. D. Robinson, “Theoretical foundations for joint digital–optical analysis of electro-optical imaging systems,” Appl. Opt. 47(10), B64–B75 (2008).

9. A. V. Gorevoy, A. S. Machikhin, V. I. Batshev, and V. Ya. Kolyuchkin, “Optimization of stereoscopic imager performance by computer simulation of geometrical calibration using optical design software,” Opt. Express 27, 17819–17839 (2019).

10. A. V. Gorevoy, A. S. Machikhin, D. D. Khokhlov, and V. I. Batshev, “Optimization of a geometrical calibration procedure for stereoscopic endoscopy systems,” Proc. SPIE 11061, 110610B (2019).

11. A.-S. Poulin-Girard, X. Dallaire, S. Thibault, and D. Laurendeau, “Virtual camera calibration using optical design software,” Appl. Opt. 53(13), 2822–2827 (2014).

12. L. Krüger and C. Wöhler, “Accurate chequerboard corner localization for camera calibration,” Pattern Recognit. Lett. 32, 1428–1435 (2011).

13. T. Yang, Q. Zhao, X. Wang, and Q. Zhou, “Sub-pixel chessboard corner localization for camera calibration and pose estimation,” Appl. Sci. 8, 2118 (2018).

14. S. Malassiotis and M. G. Strintzis, “Stereo vision system for precision dimensional inspection of 3D holes,” Mach. Vis. Appl. 15(2), 101–113 (2003).

15. S. W. Lee, S. Y. Lee, and H. J. Pahk, “Precise edge detection method using sigmoid function in blurry and noisy image for TFT-LCD 2D critical dimension measurement,” Curr. Opt. Photon. 2, 69–78 (2018).

16. M. Rosenberger, C. Zhang, P. Votyakov, M. Preißler, R. Celestre, and G. Notni, “EMVA 1288 camera characterisation and the influences of radiometric camera characteristics on geometric measurements,” Acta IMEKO, Proc. Int. Meas. Conf. 5(4), 81–87 (2016).

17. A. V. Gorevo˘ı, V. Ya. Kolyuchkin, and A. S. Machikhin, “Estimating the measurement error of the geometrical parameters of objects during the planning of stereoscopic systems,” Komp. Opt. 42(6), 985–997 (2018).

18. Z. Zhang, “Determining the epipolar geometry and its uncertainty: A review,” Int. J. Comput. Vis. 27(2), 161–195 (1998).

19. J. Immerkaer, “Fast noise-variance estimation,” Comput. Vis. Image Understanding 64(2), 300–302 (1996).

20. K. Krishnamoorthy, Handbook of Statistical Distributions with Applications (Chapman & Hall/CRC, 2006), p. 133.