ISSN 2071-8594

Russian academy of sciences

Editor-in-Chief

Gennady Osipov

D. A. Gavrilov, D. A. Lovtsov Efficient Automated Processing Visual Information Using Artificial Intelligence Technologies

Abstract.

The main provisions for solving the complex problem of effective processing of visual information in an automated optoelectronic system of ground-space monitoring using artificial intelligence technologies are presented. The stages of information processing are considered. A functional and logical decomposition of a complex problem of effective processing of visual information in an automated optoelectronic system into a hierarchical set of partial problems of less complexity is performed and variability of particular solutions is provided to obtain a rational solution to the main problem. The basic relationships and statements of the formally developed mathematical apparatus for processing information in real time are presented, on the basis of which the corresponding effective information and mathematical support has been developed. The hardware for solving the problem is presented. The results of experimental studies are presented.

Keywords:

optoelectronic system, monitoring, processing of visual information, stabilization, detection, localization, classification, functional diagnostics, efficiency.

PP. 33-46.

DOI 10.14357/20718594200404

References

1. Vizilter Yu.V., Zheltov S.Yu. Problems of technical vision in modern aviation systems // Technical vision in control systems for mobile objects - 2010: Proceedings of the scientific and technical conference-seminar. Issue 4 / Ed. R.R. Nazirova. 2011.P. 11–45.
2. Matveev I. A., Chygrynsky V. V. Optimization of a tracking system based on a network of cameras // Izvestiya RAN. Theory and control systems. 2020. No. 4. P. 110–114.
3. Smirnov A.V., Levashova T.V., Ponomarev A.V. Ontological model of decision support based on human-machine collective intelligence // Artificial Intelligence and Decision Making. 2020. No. 3. P. 48–60.
4. Knyazev V.V., Lovtsov D.A. Situational planning of secure information processing in ACS by testing complex dynamic objects // Automation and Telemechanics. 1998. No. 9. P. 166-181.
5. Gavrilov D.A., Pavlov A.V. Streaming hardware imple-mentation of the SURF algorithm // Izvestiya VUZov. Electronics. 2018. No. 5 (23). P. 502-511.
6. Mestetsky L.M. , Gavrilov D.A., Semenov A.B. A method of marking aircraft images on aerospace images based on continuous morphological models // Programming. 2019. No. 6. P. 3–12.
7. Gavrilov D.A. Hardware and software complex for testing algorithms for detecting and localizing objects in video sequences // Scientific Instrument Engineering. 2019. No. 1 (29). P. 21–27.
8. Gavrilov D.A. Neural network algorithm for automatic detection and tracking of an object of interest in a video signal // 16th National Conference on Artificial Intelligence (September 24–27, 2018, Moscow, Russia). Conference proceedings. In 2 volumes. T 2.2018, P. 188–190.
9. Pun A.B., Gavrilov D.A., Shchelkunov N.N., Fortunatov A.A. Algorithm for adaptive binarization of objects in a video sequence in real time // Success of modern radioelectronics. 2018. No. 8. P. 40–48. DOI: 10.18127 / j20700784–201809–05.
10. Gavrilov D.A. Pavlov A.V., Shchelkunov D.N. Hardware implementation of compression of the dynamic range of digital images on the Xilinx FPGA // Journal of Radioelectronics [electronic journal]. 2018. No. 10.S. http://jre.cplire.ru/jre/oct18/6/text.pdf, DOI 10.
11. Gavrilov D.A., Shchelkunov N.N. Software for marking large-format aerospace images and preparing training samples // Scientific instrument-making. 2020. No. 2 (30). P. 67–75.
12. Carvana Image Masking Challenge – 1st Place Winner’s Interview [Electronic resource]. URL: http://blog.kaggle.com/2017/12/22/carvana-image-masking-first-place-interview/.
13. Ronneberger O., Fischer P., Brox T. U-Net: Convolutional Networks for Biomedical Image Segmentation // Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015. P. 1–8. DOI: 10.1007 / 978-3-319-24574-4_28.
14. Lovtsov D.A., Gavrilov D.A. Issues of operational processing of visual information in the AOES of ground-space monitoring // Tr. VI Int. scientific-practical conf. "Information technology and nanotechnology - ITNT-20" (May 26 - 29, 2020). In 4 volumes / ISOI RAS, SNIU. - V. 2. Image processing and remote sensing of the Earth - Samara: Samara nat. issled. un-t them. acad. S.P. 2020.P. 271–276.
15. Sikorsky O.S. Review of convolutional neural networks for the problem of image classification // New information technologies in automated systems. 2017. No. 20. P. 37–42.
16. Szegedy C., Ioffe S., Vanhoucke V., Alemi A. Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning 2016. DOI: 10.1016 / j.patrec.2014.01.008.
17. AutoML [Electronic resource]. URL: https://www.automl.org/.
18. Zoph B., Vasudevan V., Shlens J., Le V.Q. Learning transferable frchitectures for scalable image recognition // IEEE / CVF Conference on Computer Vision and Pattern Recognition. 2018.P. 8697–8710.
19. Krizhevsky A., Nair V., Hinton G. The CIFAR-10 dataset [Electronic resource]. URL: https://www.cs.toronto.edu/~kriz/cifar.html.
20. Berg A., Deng J., Fei-Fei L. ImageNet Large Scale Visual Recognition Competition (ILSVRC) [Electronic resource]. URL: http://www.image-net.org/challenges/LSVRC/.
21. COCO [Electronic resource]. URL: http://cocodataset.org/#home.
22. Favreau J.-D., Lafarge F., Bousseau A., Auvolat A. Extracting Geometric Structures in Images with Delaunay Point Processes // IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers. 2019. No. 4 (42). P. 837-850. DOI: 10.1109 / TPAMI.2018.2890586.
23. Pat. 2714182, RF Patent No. 2714182 Hardware and soft-ware complex for testing systems for automatic and / or semi-automatic detection and localization of objects in sequence / D.A. Gavrilov (RF). No. 2018135058; Application 10/05/2018; Publ. 13.02.2020. Bul. No. 5.
24. Gavrilov D. A. Quality assessment of object detection and localization in a video stream / / Bulletin of Bauman Moscow state technical University. instrument Engineering series, Moscow: Bauman Moscow state technical University, 2019, no. 2, P. 40-55.
25. Google Earth on the Internet [Electronic resource]. URL: https://www.google.com/earth/.
26. SASGIS Web-cartography and navigation [Electronic resource]. URL: http://www.sasgis.org/