Skip to main content
Log in

Mathematical Model of the Human Visual System

  • Published:
Optical Memory and Neural Networks Aims and scope Submit manuscript

Abstract

A mathematical model of visual system of the human observing images on optoelectronic device display is proposed. The model allows to formalize in linear approximation the physiological processes of registration and transformation of halftone object images in the human visual system in the presence of external and internal noise, and to estimate the detection probability of objects visual images in the form of Johnson’s equivalent bar patterns. On the basis of proposed model mathematical expressions for the visual system contrast sensitivity function are derived. Experimental studies on the measurement of this characteristic are carried out. A satisfactory agreement between the calculated and experimental results indicates the adequacy of the proposed mathematical model for the accepted restrictions on its applicability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.

Similar content being viewed by others

REFERENCES

  1. Lloyd, J.M., Thermal Imaging Systems, New York: Plenum Press, 1975.

    Book  Google Scholar 

  2. Sokolov, M.E., Tel’nykh, A.A., Koval’chuk, A.V., et al., Opt. Mem. Neural Networks, 2009, vol. 18, p. 1. https://doi.org/10.3103/S1060992X09010019.

    Article  Google Scholar 

  3. Filippov, I.Y., Kovalev, M.S., Krasin, G.K., et al., Opt. Mem. Neural Networks, 2018, vol. 27, p. 32. https://doi.org/10.3103/S1060992X18010022.

    Article  Google Scholar 

  4. Mosyagin, G.M., in Theory of Optoelectronic Systems, Mosyagin, G.M., Nemtinov, V. B., and Lebedev, E.N., Eds., Moscow: Mechanical Engineering, 1990.

    Google Scholar 

  5. Papoulis, A., Systems and Transforms with Applications in Optic, New York: McGraw-Hill, 1968.

    Google Scholar 

  6. Glezer, V.D., Zrenie i myshlenie (Sight and Thinking), Leningrad: Nauka, 1985.

    Google Scholar 

  7. Hubel, D.H., Eye, Brain and Vision, Scientific American Library, 1988.

    Google Scholar 

  8. Barten, P.G.J., Contrast Sensitivity of the Human Eye and Its Effects on Image Quality, Knegsel: HV Press, 1999.

  9. Bondarko, V.M., Danilova, M.V., Krasil’nikov, N.N., Leushina, L.I., Nevskaya, A.A., and Shelepin, Yu.E., Spatial Vision, St. Petersburg: Nauka, 1999.

    Google Scholar 

  10. Shelepin, Yu.E. and Krasil’nikov, N.N., Contrast sensitivity of the visual system in the presence of external noise, Perception, 1996, vol. 25, suppl., p. 110.

    Article  Google Scholar 

  11. Shelepin, Y.E., Krasil’nikov, N.N., Krasil’nikova, O.I., and Chihman, V.N., What visual perception model is optimal in terms of signal-to-noise ratio?, SPIE, 2000, vol. 3981, pp. 161–169.

    Google Scholar 

  12. Somia Mostafa El-Hefnawy and Abed Nasr, Mathematical modeling of human eye retina for solving edge-detection problem, Proc. SPIE 3817, Parallel and Distributed Methods for Image Processing III, 1999. https://doi.org/10.1117/12.365899.

  13. Krasil’nikov, N.N., Krasil’nikova, O.I., and Shelepin, Y.E., Mathematical model of the color constancy of the human visual system, J. Opt. Technol., 2002, vol. 69, no. 5.

  14. Applications of Optical Fourier Transforms, Stark, H., Academic Press, 1982.

  15. Goodman, J.W., Introduction to Fourier Optics, Department of Electrical Engineering, Sanford University, 1968.

    Google Scholar 

  16. Rose, A., Vision Human and Electronic, New York: Plenum Press, 1973.

    Google Scholar 

  17. Venttsel, E.S. and Ovcharov, L.A., Theory of Probability and Its Engineering Applications, Moscow: Science, 1988.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Y. S. Gulina, V. Ya. Koliuchkin or N. E. Trofimov.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gulina, Y.S., Koliuchkin, V.Y. & Trofimov, N.E. Mathematical Model of the Human Visual System. Opt. Mem. Neural Networks 27, 219–234 (2018). https://doi.org/10.3103/S1060992X1804001X

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S1060992X1804001X

Keywords:

Navigation