SIGNAL DISCREPANCY ESTIMATION IN EQUIVALENT REPRESENTATION PROBLEM OF DISCRETE SYSTEM

Samoilenko Marina   V.

2017 , VOLUME 17, NUMBER 4 ( July-August )

ISSN 2226-1494 (print), ISSN 2500-0373 (online)

Publications

Editor-in-Chief

Nikiforov
Vladimir O.
D.Sc., Prof.

Partners

doi: 10.17586/2226-1494-2017-17-4-651-657

SIGNAL DISCREPANCY ESTIMATION IN EQUIVALENT REPRESENTATION PROBLEM OF DISCRETE SYSTEM

M. V. Samoilenko

Read the full article

Article in Russian

For citation: Samoilenko M.V. Reconstruction of point objects spatial coordinates from two-dimensional images. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2017, vol. 17, no. 4, pp. 651–657 (in Russian). doi: 10.17586/2226-1494-2017- 17-4-651-657

Abstract

The paper presents a method of reconstruction of spatial coordinates for the point objects, located in free space, together with their number and radiation light intensity. The required information to be measured consists of the stereo images of the observed area received by the television or thermal imaging system. The image planes spatial positions are taken to be known. The method is based on the tomography approach in signal processing. For its implementation the observed space area is divided into resolution elements with known spatial coordinates. Resolution element size specifies determination accuracy of the object spatial coordinates. The suggested method makes it possible to restore a vector of optical radiation intensity distribution over the resolution elements of the observed area. This vector contains the information on the number ВОССТАНОВЛЕНИЕ ПРОСТРАНСТВЕННЫХ КООРДИНАТ ТОЧЕЧНЫХ ОБЪЕКТОВ… Научно-технический вестник информационных технологий, механики и оптики, 2017, том 17, № 4 652 and spatial coordinates of objects as well as their radiation power. Component numbers with values that exceed the background level are the numbers of resolution elements with the objects, the amount of such components is the amount of objects, while their values determine the radiation intensity. The main advantage of the method is that it does not require points identification on the images for solving the problem. No active scanners or range measured channels are required that gives the possibility for the passive object observation. The breadth of view limits of image registration systems enables to solve simultaneously both the tasks of detection and reconstruction of spatial coordinates of objects in the observed space area

Keywords: tomography approach, point objects, two-dimensional images, spatial coordinates, reconstruction

References

1. Ustinov N.D., Matveev I.N., Protopopov V.V. Methods for Optical Fields Processing in Laser Locations. Moscow, Nauka Publ., 1983, 272 p. (In Russian)

2. Molebnyi V.V. Optical-Location Systems. Moscow, Mashinostroenie Publ., 1981, 181 p. (In Russian)

3. Starovoitov E. Modern technical tools of passive optical location. Sovremennaya Elektronika, 2011, no. 2, pp. 40–43. (In Russian)

4. Lebed'ko E.G. Sistemy Opticheskoi Lokatsii: Uchebnoe Posobie [Systems of Optical Ranging. Textbook]. Part 2. St. Petersburg, NIU ITMO Publ., 2012, 129 p.

5. Zubar A.V., Maistrenko V.A., Kaikov K.V. Hardwaresoftware implementation of optical-electronic stereo system for determination of distance. Omsk Scientific Bulletin, 2013, no. 3, pp. 273–277.

6. Fursov V.A., Goshin Y.V. Information technology for digital terrain model reconstruction from stereo images. Computer Optics, 2014, vol. 38, no. 2, pp. 335–342. (In Russian)

7. Egorov I.V., Lachugin D.V. Method of choosing the optimal parameters combination of machine vision system based on three cameras. Vestnik Saratov State Technical University, 2012, vol. 1, no. 2, pp. 393–397. (In Russian)

8. Nazarov A.S. Photogrammetry. Minsk, TetraSistems Publ., 2006, 368 p. (In Russian)

9. Hartley R., Zisserman A. Multiple View Geometry in Computer Vision. 2nd ed. Cambridge University Press, 2000. 672 p.

10. Korotaev V.V., Djamiykov T.S., Nguyen H.V., Yaryshev S.N. Method for determining the spatial coordinates in the active stereoscopic system. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2014, no. 6, pp. 48–53. (In Russian)

11. Salvi J., Pages J., Batlle J. Pattern codification strategies in structured light systems. Pattern Recognition, 2004, vol. 37, no. 4, pp. 827849. doi: 10.1016/j.patcog.2003.10.002

12. Geng J. Structured-light 3D surface imaging: a tutorial. Advances in Optics and Photonics, 2011, vol. 3, pp. 128–160. doi: 10.1364/AOP.3.000128

13. Bleyer M., Gelautz M. A layered stereo matching algorithm using image segmentation and global visibility constraints. ISPRS Journal of Photogrammetry and Remote Sensing, 2005, vol. 59, no. 3, pp. 128–150. doi: 10.1016/j.isprsjprs.2005.02.008

14. Ogale A., Aloimonos Y. Shape and the stereo correspondence problem. International Journal of Computer Vision, 2005, vol. 65, no. 3, pp. 147162. doi: 10.1007/s11263-005-3672-3

15. Samoilenko M.V. Signal Processing in Problems of Location Measurements and Estimation. Moscow, Spektr Publ., 2016, 260 p. (In Russian) 16. Samoilenko V.I., Puzyrev V.A., Grubrin I.V. Technical Cybernetics. Moscow, MAI Publ., 1994, 280 p. (In Russian)

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License