Designing Recolorization Algorithms to Help People with Color Vision Anomalies
https://doi.org/10.35596/1729-7648-2023-21-1-12-18
Abstract
The problem of perception of visual information by people with color vision anomalies remains quite relevant, as evidenced by the interest in studying this problem not only in medicine, but also in the field of medical technology. Researchers around are working on the task to create algorithms and software that can transform images and videos in accordance with their correct perception by people with color blindness. However, today there are no algorithms that allow people with any type, form, and degree of color vision anomaly to correctly perceive the visual information surrounding them. Based on the considered advantages and disadvantages of existing algorithms, conclusions were drawn about the requirements for the designed recoloring algorithms, which are planned to be implemented in software to help people with color perception issues. Such algorithms will not only allow correct video conversion for people with dichromacy and monochromacy but will also enable users with any degree of anomalous trichromacy to perceive the world around them most accurately. In addition, these algorithms will be distinguished by the high speed of the recolorization process, and the “naturalness” of the colors obtained in the process of transformations.
About the Authors
V. V. SinitsynaBelarus
Sinitsyna Vlada Vladislavovna, Postgraduate at the Engineering Psychology and Ergonomics Department
220013, Minsk, P. Brovka St., 6
+375 44 770-85-18
A. M. Prudnik
Belarus
Cand. of Sci., Associate Professor, Associate Professor at the Engineering Psychology and Ergonomics Department
220013, Minsk, P. Brovka St., 6
References
1. Shiffman H. R. (2003) Sensation and Perception. Saint Petersburg, Piter Publ. (in Russian).
2. Chaparro A., Chaparro M. (2017) Applications of Color in Design for Color-deficient Users. Journal of Ergonomics in Design: the Quarterly of Human Factors Applications. 25, 23–30. DOI: 10.1177/1064804616635382.
3. Zhu Z., Toyoura M., Go K., Kashiwagi K., Fujishiro I., Wong T.-T., Mao X. (2021) Personalized Image Recoloring for Color Vision Deficiency Compensation. IEEE Transactions on Multimedia. 24, 1721–1734. DOI: 10.1109/TMM.2021.3070108.
4. Yang S., Wong E. K. (2008) Quantification and Standardized Description of Color Vision Deficiency Caused by Anomalous Trichromats. Part II: Modeling and Color Compensation. EURASIP Journal on Image and Video Processing. 2008, 1–12. DOI: 10.1155/2008/246014.
5. Zhu Z., Mao X. (2021) Image Recoloring for Color Vision Deficiency Compensation: a Survey. The Visual Computer. 37, 2999–3018. DOI: 10.1007/s00371-021-02240-0.
6. Evans R. M. (1964) An Introduction to Color. Moscow, Mir Publ. (in Russian).
7. Batai L. E., Gursky A. L., Mironchik V. V. (2015) Measurements in Laser and Optoelectronic Systems. In 3 p. P. 1: Photometric and Colorimetric Measurements. Minsk, BGUIR Publ. (in Russian).
8. Ribeiro M., Gomes A. J. P. (2019) Recoloring Algorithms for Colorblind People: a Survey. ACM Comput. Surv. 52, 1–37. DOI: 10.1145/3329118.
Review
For citations:
Sinitsyna V.V., Prudnik A.M. Designing Recolorization Algorithms to Help People with Color Vision Anomalies. Doklady BGUIR. 2023;21(1):12-18. (In Russ.) https://doi.org/10.35596/1729-7648-2023-21-1-12-18