Skip to main content
Log in

Search-Detection-Recognition: Simulation via Thermal Images with Varying Quality

  • MATHEMATICAL SIMULATION
  • Published:
Journal of Computer and Systems Sciences International Aims and scope

Abstract

We propose an algorithm of a dynamical model for the search-detection-recognition of objects by the onboard thermal-imaging systems operating in the wavelength ranges from 3 to 5 µm and 8 to 12 µm. We provide the main simulation results under the action with respect to ground objects, analyzing the influence of the main agents on the probabilistic-range characteristics of the scene–optical route–thermal-imaging channel–person system under the assumption that the image quality varies within the search because the carrier approaches the object.

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.

Fig. 1.
Fig. 2.
Fig. 3.

Similar content being viewed by others

Notes

  1. The Heaviside function has the form \(\theta (x) = \left\{ \begin{gathered} 1,\quad x > 0, \hfill \\ 0,\quad x \leqslant 0. \hfill \\ \end{gathered} \right.\)

REFERENCES

  1. G. Witus, G. Gerhard, and R. D. Ellis, “Contrast model for three-dimensional vehicles in natural lighting and search performance analysis,” Opt. Eng. 40, 1858–1868 (2001).

    Article  Google Scholar 

  2. M. H. Friedman, “Fundamental search relationships and their application to field regard search, search by multiple observers search from moving vehicle and multitarget search,” Opt. Eng. 52, 1107–1117 (2013).

    Article  Google Scholar 

  3. V. P. Ivanov, V. I. Kurt, and V. A. Ovsyannikov, Modeling and Evaluation of Modern Thermal Imaging Devices (Otechestvo, Kazan’, 2006) [in Russian].

  4. V. A. Ovsyannikov, Ya. V. Ovsyannikov, and V. L. Filippov, “Battlefield jamming computer simulation,” Oboron. Tekh., Nos. 4–5 (2012).

  5. V. A. Ovsyannikov, Ya. V. Ovsyannikov, and V. L. Filippov, “Assessment and improvement of the efficiency of using ground-based thermal imaging devices in a dynamic mode of operation,” Oboron. Tekh., No. 7, 49–63 (2015).

  6. M. S. Shekhter, Psychological Problems of Recognition (Moscow, Prosveshchenie, 1967) [in Russian].

    Google Scholar 

  7. A. V. Luizov, Eye and Light (Energoatomizdat, Leningrad, 1983) [in Russian].

    Google Scholar 

  8. V. F. Rubakhin, Psychological Foundations of Primary Information Processing (Nauka, Leningrad, 1974) [in Russian].

    Google Scholar 

  9. Perception: Mechanisms and Models: Readings from Scientific American (W. H. Freeman, San Francisco, 1972).

  10. N. N. Krasil’nikov, The Theory of Transmission and Perception of Images. Image Transmission Theory and its Applications (Radio Svyaz’, Moscow, 1986) [in Russian].

    Google Scholar 

  11. V. L. Levshin, Biocybernetic Optical-Electronic Devices for Automatic Image Recognition (Mashinostroenie, Moscow, 1987) [in Russian].

    Google Scholar 

  12. L. G. Evsikova, “Threshold contrasts of the visual system,” Opt.-Mekh. Prom-st’, No. 9, 49–53 (1983).

  13. Visual Perception of Images, Toolkit, No. 10 of Tr. GOI im. S. I. Vavilova, Ser.: Optical Image Processing (GOI im. S. I. Vavilova, Leningrad, 1990) [in Russian].

  14. A. A. Khorev, Theoretical Foundations for Assessing the Capabilities of Technical Means of Reconnaissance (MO RF, Moscow, 2000) [in Russian].

    Google Scholar 

  15. N. P. Travnikova, Visual Search Efficiency (Moscow, Mashinostroenie, 1986) [in Russian].

    Google Scholar 

  16. A. A. Khorev, “Appraisal of visual and optical reconnaissance capabilities,” Spets. Tekh., No. 6, 44–54 (2010).

  17. V. A. Ovsyannikov, Ya. V. Ovsyannikov, and V. L. Filippov, “Optimization of the movement of the carrier of search air thermal imaging equipment,” Oboron. Tekh., Nos. 1–2, 41–51 (2014).

    Google Scholar 

  18. E. S. Ventsel’, Operations Research (Sov. Radio, Moscow, 1972) [in Russian].

  19. C. Gerald, Holst Electro-Optical Imaging System Performance, 5th ed. (JCD Publ., SPIE Press, New York, 2008), Vol. PM187.

  20. A. L. Vorob’ev, Yu. P. Zhurik, A. M. Krasnov, and A. V. Kudimov, “Methods of probabilistic analysis of the surveillance processing digital thermal imaging systems,” Inform.-Izmerit. Upravl. Sist. 13 (8), 67–81 (2015).

    Google Scholar 

  21. M. Volimer and K. Mollman, Infrared Thermal Imaging: Fundamentals, Research and Applications (Wiley, New York, 2010).

    Book  Google Scholar 

  22. G. M. Aleev, V. P. Ivanov, and V. A. Ovsyannikov, Non-Scanning Thermal Imaging Devices. Fundamentals of Theory and Calculation (Kazansk. Univ., Kazan’, 2004) [in Russian].

  23. V. P. Ivanov, Applied Atmospheric Optics (Novoe Znanie, Kazan’, 2000) [in Russian].

  24. N. N. Kulakova and S. V. Mishin, “Analysis of the results of the calculation ranges of detection, recognition and identification of thermal imaging system by two methods,” Kotnenant 14 (1), 49–53 (2015).

    Google Scholar 

  25. V. L. Filippov, “Taking into account variations in ‘optical weather’ when substantiating the tactical and technical characteristics of optoelectronic systems,” Oboron. Tekh., Nos. 1–2, 13–21 (2007).

    Google Scholar 

Download references

Funding

This study is supported by the Russian Foundation for Basic Research, grant nos. 20-08-00949-a (Sections 1, 2, and 4) and 19-29-06077-mk (Section 3).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to N. K. Obrosova.

Additional information

Translated by A. Muravnik

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vishnyakova, L.V., Kim, V.Y., Obrosov, K.V. et al. Search-Detection-Recognition: Simulation via Thermal Images with Varying Quality. J. Comput. Syst. Sci. Int. 59, 905–917 (2020). https://doi.org/10.1134/S106423072006012X

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S106423072006012X

Navigation