Development and manufacture of a color calibration measure based on the use of color optical glasses

Sagatelyan, G.R., Piskunova E.R., Solomashenko A.B., Afanasyeva O.L., Kuznetsov, A.S.

For Russian citation (Opticheskii Zhurnal):

Сагателян Г.Р., Пискунова Е.Р., Соломашенко А.Б., Афанасьева О.Л., Кузнецов А.С. Разработка и изготовление цветовой калибровочной меры на основе применения цветных оптических стёкол // Оптический журнал. 2025. Т. 92. № 12. С. 45–56. http://doi.org/10.17586/1023-5086-2025-92-12-45-56

Sagatelyan G.R., Piskunova E.R., Solomashenko A.B., Afanasyeva O.L., Kuznetsov A.S. Development and manufacture of a color calibration measure based on the use of color optical glasses [in Russian] // Opticheskii Zhurnal. 2025. V. 92. № 12. P. 45–56. http://doi.org/10.17586/1023-5086-2025-92-12-45-56

For citation (Journal of Optical Technology):

Abstract:

The subject of the study. Identification of the image color based on the application of the set of reference colors optical glasses (color calibration measure) from a large set of light filters without using spectrometers. The purpose of the work. Development of the design and manufacturing process of a color calibration measure for color identification based on the distribution of the relative brightness of the red, green and blue colors of the image. Method. Using the RGB model to obtain the coordinates of a color cube based on the analysis of color diagrams of the relative brightness distribution of the corresponding colors. Main results. The use of the developed color calibration measure in combination with the white color standard makes it possible to identify the color of an optical microscopic image in relation to a specific combination of the properties of the CCD sensor of a video camera and the display of a computerized microscope, as well as the features of the alignment of its optical system. Practical significance. The proposed design and manufacturing process of the color calibration measure make it possible to provide mass preliminary diagnosis of the presence of pathology in an automated mode of viewing histological micro-preparations without the involvement of medical personnel themselves.

Keywords:

color calibration measure, color cube, white standard, chromaticity diagram, light filters, optical spectra, optical microscope, RGB system, XYZ system

Acknowledgements:

the study was carried out within the framework of the “PRIORITY 2030” program

OCIS codes: 150.1708, 330.1710

References:

1. Kravtsova T.A., Dobrolubova D.A., Samorodov A.V. Comparatively studied color correction methods for color calibration of automated microscopy complex of biomedical specimens // Science & Education of the
Bauman MSTU. 2016. № 2. P. 91–104. https://doi.org/10.7463/0216.0833329
2. Lozhkin L.D., Tabakov D.P. Color in television-its reproduction and perception // Journal of Optical Technology. 2018. V. 85. № 7. P. 419–424. https://doi.org/10.1364/JOT.85.000419
3. Beliaeva, A.S., Romanova G.E., Sharikova M.O. Estimation of color reproduction accuracy using a tunable source based on an acoustic-optical tunable filter // Journal of Optical Technology. 2023. V. 90. № 11. P. 660. https://doi.org/10.1364/JOT.90.000660

4. Immunocytochemical detection of brain neurons using the selective marker Neu N / Korzhevskii D.É., Gilerovich E.G., Zin’kova N.N. et al. // Neuroscience and Behavioral Physiology. 2006. V. 36. № 8. P. 857–859. https://doi.org/10.1007/s11055-006-0098-5
5. Ermachenkova M.K., Malashin R.O., Boiko A.A. Neural network training for thermal image classification based on visible spectrum images [In Russian] // Journal of Optical Technology. 2023. V. 90. № 10. P. 590–600. https://doi.org/10.1364/JOT.90.000590
6. Ramos-Vara J.A. Technical aspects of immunohistochemistry // Veterinary Pathology. 2005. V. 42. P. 405–426. https://doi.org/10.1354/vp.42-4-405
7. Histological dyes and reagents Premium ООО7. Electronic resource URL: https://biovitrum.ru/files/kraski_mail.pdf ?ysclid=m6qwp2hzvi307785902 ( “BioVitrum” LLC / Premium Histological dyes and reagents)
8. Makhov D.S., Sagatelyan G.R., Samorodov A.V. Color calibration slide for digital microscopy systems // Measurement Techniques. 2021. № 10. P. 60–64. https://doi.org/10.32446/0368-1025it.2021-10-60-64
9. Arbeláez D.V.O., Rodríguez E.S., Montes J.O.G. Design, assembly and start-up of an experimental setup for optical characterization in biological tissues // Journal of Engineering Research. 2023. V. 3. № 27. 8 p. https://doi.org/10.22533/at.ed.3173272314085
10. Gorbunova E.V., Sycheva E.A., Chertov A.N. Colorimetry. Guidelines for performing laboratory work. Part 1. Color vision and the basics of calculating the color of radiation sources. Educational and methodical manual [in Russian]. St. Petersburg: ITMO University, 2021. P. 26–47.
11. Electronic resource URL: https://www.alliedhightech.com/Media/Default/EquipmentBrochures/AxioImager %20Vario%20-%20long%20brochure.pdf (Carl Zeiss MicroImaging GmbH / Axio Imager Vario long brochure)
12. Electronic resource URL: https://www.microscopeworld.com/images/Brochures/Zeiss_Axio-ImagerVario-brochure.pdf (Carl Zeiss Microscopy GmbH / ZEISS Axio Imager Vario Product Information)
13. Gaudin J. Colorimetry in video processing: 23 interactive experiences [in Russian] / Translated from French by A.L. Laut. Moscow: Technosphere Publ., 2008. 324 p.
14. Application of optical methods to estimate physiological damage to wheat flag leaves / Baranova E.N., Shelepova O.V., Zolotukhina A.A. et al // Photonics. 2024. V. 18. № 4. P. 320–330. https://doi.org/10.22184/1993-7296.FRos.2024.18.4.320.330
15. Shapiro L.D., Stockman G.C. Computer vision. Electronic Resource. Translated from English. Moscow: BINOM. Laboratory of Knowledge, 2015. P. 252–254. https://djvu.online/file/aVuCTvxRIF4Bg?ysclid=mfti14fxvw864307601 (date of request 21.09.2025)
16. Electronic resource URL: https://www.elektrosteklo.ru/Catalog.htm (Production company LLC “Elektrosteklo” / Product catalog)
17. Zuikov I.E., Savkova E.N. Colorimetry with high spatial resolution [in Russian] // Instruments and measurement methods. 2013. № 1(6). P. 86–91.
18. Electronic resource URL: https://scarse.sourceforge. net/docs/kodak/Q60-tech.pdf (Kodak Q-60 color input targets. Technical Data/Color Paper // Kodak publication No. TI-2045. June 2003).
19. Sipaila S.U. Increasing the accuracy of color reproduction of real pictorial originals at the scanning stage [in Russian] // Proceedings of BSTU. 2024. V. 4. № 2 (285). P. 47–52. https://doi.org/10.52065/2520-6729-2024-285-6

20.Sagatelyan G.R., Piskunova E.R., Kondratenko V.S., Kuznetsov A.S. Development of the model of a set of color standards for optical microscope research and its manufacturing technology [in Russian] // Instrumentation. 2023. 2023. № 8. P. 40–43. http://i.uran.ru/webcab/system/files/journalspdf/pribory/pribory2023-no-8/pribory238.pdf (accessed 21.09.2025)
21. Sagatelyan G.R., Piskunova E.R., Kuznetsov A.S., Solomashenko A.B. Technological provision of geometric characteristics of precision optical parts by the methods of abrasive lapping // Proceedings of the XIII International Conference on Photonics and Information Optics. 2024. P. 569–570. URL: https://openrepository.mephi.ru/handle/123456789/12380 (accessed 09/21/2025)
22. Sagatelyan G.R., Piskunova E.R., Dubovik N.N., Kuznetsov A.S. Investigation of the kinematics of a new machine for double-sided polishing of optical planeparallel plates [in Russian] // Nanotechnology: the development, application – XXI Century. 2022. V. 14. № 3. P. 47–55. https://doi.org/10.18127/j22250980-202203-06