DOI: 10.17586/1023-5086-2025-92-06-55-65

A study on the background noise error of autocollimator based on Retinex theory

Di K., Ma, L., Li Renpu, Wang Zhao Yang, Yuan Jun Sen, Huo Yu Jia, Liu Shi Long, Wang Jia Mei

For Russian citation (Opticheskii Zhurnal):

Ke Di, Zhao Yang Wang, Jun Sen Yuan, Yu Jia Huo, Long Ma, Shi Long Liu, Jia Mei Wang, Ren Pu Li. A study on the background noise error of autocollimator based on Retinex theory (Исследование фоновой шумовой погрешности автоколлиматора, основанное на теории ретинекса) [на англ. языке] // Оптический журнал. 2025. Т. 92. № 6. С. 55–65. http://doi.org/10.17586/1023-5086-2025-92-06-55-65

Ke Di, Zhao Yang Wang, Jun Sen Yuan, Yu Jia Huo, Long Ma, Shi Long Liu, Jia Mei Wang, Ren Pu Li. A study on the background noise error of autocollimator based on Retinex theory (Исследование фоновой шумовой погрешности автоколлиматора, основанное на теории ретинекса) [in English] // Opticheskii Zhurnal. 2025. V. 92. № 6. P. 55–65. http://doi.org/10.17586/1023-5086-2025-92-06-55-65

For citation (Journal of Optical Technology):

Abstract:

Subject of study. Autocollimation measurement system is the main means to realize precision angle measurement, but multifaceted error sources limit the further improvement of autocollimator angle measurement accuracy. The purpose of the work. This paper focuses on a kind of reflection noise induced from the non-working optical structure surface inside the autocollimator. This noise source can lead to errors in the detection of the target image by the image sensor. Method. Combined with the principle of Hough transform image recognition, we propose to utilize the Retinex theory to compensate the reflection noise inside the autocollimator. Main results. It is experimentally verified that this compensation algorithm can effectively suppress the influence of noise on imaging detection, and the measurement accuracy of the autocollimator around the X-axis and Y-axis can be improved from 4.29І and 3.87І to 3.59І and 3.15І. System measurement stability performance is also improved, about 11.99% and 15.75% in the X-axis and Y-axis directions, as well. Practical significance. Therefore, this algorithmic compensation method can effectively enhance the measurement performance of the autocollimator.

Keywords:

optical autocollimator, angle measurement, error calibration, Retinex algorithm optimization

Acknowledgements:

National Natural Science Foundation of China (62375031); National Key Research and Development Program of China (2021YFC2203601)

OCIS codes: 120.1680, 120.4570, 120.4630

References:

1. Eves B.J., Leroux I.D. Autocollimators: plane angle measurand ambiguities and the impact of surface form // Metrologia. 2023. V. 60. № 6. P. 065001. https://doi.org/10.1088/1681-7575/acf9a8

2. Chaturaporn K., Surasak K., Sakchai C. et al. A calibration method of CMOS-based autocollimator using reflected diffraction pattern of strip reflector // Precision Engineering. 2023. V. 85. P. 191–196. https://doi.org/10.1016/j.precisioneng.2023.10.004

3. Chen Y., Shimizu Y., Tamada J. et al. Optical frequency domain angle measurement in a femtosecond laser autocollimator // Optics express. 2017. V. 25. № 14. P. 16725–16738. https://doi.org/10.1364/OE.25.016725

4. Larichev R.A., Filatov Y.V. A model of angle measurement using an autocollimator and optical polygon // Photonics. 2023. V. 10. № 12. P. 1359. https://doi.org/10.3390/photonics10121359

5. Ma W., Li J., Liu S. et al. An autocollimator axial measurement method based on the strapdown inertial navigation system // Sensors. 2024. V. 24. № 8. P. 2590. https://doi.org/10.3390/s24082590

6. Ralf G.D., Matthias S., Andreas J. et al. A comparison of traceable spatial angle autocollimator calibrations performed by PTB and VTT MIKES // Metrologia. 2022. V. 59. № 2. P. 024002. https://doi.org/10.1088/1681-7575/ac42b9

7. Kaewpho S., Kerdkaew C., Samnasen K. et al. An application of autocollimator for strip surface profile measurement // Journal of Physics: Conference Series. 2023. V. 2431. № 1. P. 012022. https://doi.org/10.1088/1742-6596/2431/1/012022

8. Yang Y., Zhao M., Zheng Y. et al. Method for parallelism measurement of geometrical waveguides based on the combination of an autocollimator and a testing telescope // Optics express. 2022. V. 30. № 25. P. 44518–44532. https://doi.org/10.1364/OE.475634

9. Kachkanov V., Ziesche R., Wagner U.H. et al. Optical autocollimator for vibration measurements at Diamond I13 beamline // Journal of Physics: Conference Series. 2022. V. 2380. № 1. P. 012075. https://doi.org/10.1088/1742-6596/2380/1/012075

10. Konyakhin I.A., Smekhov A. Survey of illuminance distribution of vignetted image at autocollimation systems by computer simulation // Eighth International Symposium on Precision Engineering Measurement and Instrumentation. 2013. V. 8759. P. 87593F-87593F-6. https://doi.org/10.1117/12.2014609

11. Konyakhin I.A., Polyakov V.M., Vorona A.M. Research on the methods to compensate the systematic error at optical autoreflection angular measurements // J Phys Conf Ser. 2006. V. 48. P. 932–936. https://doi.org/10.1088/1742-6596/48/1/176

12. Bergues G.J., Canali L., Schurrer C. et al. Electronic interface with vignetting effect reduction for a Nikon 6B/6D autocollimator // IEEE Trans. Instrum. Meas. 2015. V. 64. № 12. P. 3500–3509. https://doi.org/10.1109/TIM.2015.2444263

13. Bergues G.J., Schurrer C., Brambilla N. Uncertainty determination of the set Nikon 6B autocollimator plus visual interface // IEEE Trans. Instrum. Meas. 2018. V. 67. № 5. P. 1058–1064. https://doi.org/10.1109/TIM.2017.2782003

14. Zheng L., Zhang H., Qi E. et al. Characterized environmental influences on autocollimator measurement uncertainty using an extended Allan variance // Optics and Lasers in Engineering. 2024. V. 172. P. 107863. https://doi.org/10.1016/j.optlaseng.2023.107863

15. Shan X., Wang Q., Han J. et al. High-accuracy parallelism measurement of coated cube by dual-autocollimators // Measurement Science and Technology. 2023. V. 34. № 6. P. 065006. https://doi.org/10.1088/1361-6501/acbb94

16. Feng T., Yan J., Liu L. et al. Research on calibration method of MEMS gyroscope mounting error based on large-range autocollimator // IEEE Sensors Journal. 2023. V. 23. № 18. P. 21197–21207. https://doi.org/10.1109/JSEN.2023.3303254

17. Chen H., Chen R., Ma L. et al. Single-image dehazing via depth-guided deep Retinex decomposition // The Visual Computer. 2023. V. 39. № 11. P. 5279–5291. https://doi.org/10.1007/s00371-022-02659-z

18. Shen Y., Hu X., Wang T. et al. CNN-based automated trace editing method using Hough transform // Applied Geophysics. 2023. V. 20. № 3. P. 252–261. https://doi.org/10.1007/s11770-023-1068-1