Diffraction phenomenon description method based on by the topological objects set and the algorithm for distinguishing the minimum from zero intensity

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DOI: https://doi.org/10.20998/2522-9052.2020.3.03
Keywords:
diffraction, topological objects, identification, segmentation

Main Article Content

Ganna Khoroshun
Volodymyr Dahl East Ukrainian National University, Severodonetsk
https://orcid.org/0000-0002-1272-1222

Abstract

Diffraction phenomenon describing method based on the topological objects set by means of system analysis was developed in the work. Diffraction field topological objects are maximum, minimum and zero intensity, which is identical to the phase singularity or optical vortex. Topological objects mathematical representation by standard extremum search function methods was considered. The algorithm for distinguishing the minimum has been developed and zero intensity at the experimental images due to the algorithm the diffractive optical images classification possibility by the number of phase singularities without further interference analysis was shown. To increase the speed of data analyses the image segmentation method is suggested. Otained results and recommendations applying is possible in various fields of medicine and technology, which use laser radiation.

Article Details

How to Cite
Khoroshun, G. (2020). Diffraction phenomenon description method based on by the topological objects set and the algorithm for distinguishing the minimum from zero intensity. Advanced Information Systems, 4(3), 17–21. https://doi.org/10.20998/2522-9052.2020.3.03
Issue
Vol. 4 No. 3 (2020): Advanced Information Systems
Section
Identification problems in information systems
Author Biography

Ganna Khoroshun, Volodymyr Dahl East Ukrainian National University, Severodonetsk

PhD (Optics and Laser Physics), Associated Professor of Department of Construction, Urban and Spatial Planning

References

Leontovich, M.A. and Fock, V.A. (1946), “Solution of the problem of the propagation of electromagnetic waves along the earth's surface by the method of parabolic equation”, Journal of Experimental and Theoretical Physics, Vol. 16, no. 7, p. 557.

Matveev, А.А. (1988), Optics, Mir, Moscow. 445 p.

Reinhard, Voelkel (2014), Micro-Optics: Enabling Technology for Illumination Shaping in Optical Lithography, SPIE, 9052, DOI: https://doi.org/10.1117/12.2046116.

Coullet, P., Gil L. and Rocca, F. (1989), “Optical vortices”, Optics Communications, Vol. 73, p. 403.

Zhao, J. (2015), Curved singular beams for three-dimensional particle manipulation, Sci. Rep. 5, 12086; DOI:

https://doi.org/10.1038/srep12086.

Kvyetnyi, R.N. and Reminnyi, O.A. (2009), “High-speed image classification method”, Opto-electronic information and energy technologies, No. 2, pp. 22-27.

Chetyrbok, P.V. (2008), “Associative Memory and Scalar Criterion for Recognition”, Proceedings of the X International Scien-tific and Technical Conference "System Analysis and Information Technologies", NTUU "KPI", Kyiv, p. 266.

Shvorov, S.A., Shtepa, V.M. and Zayets, N.A. (2014), “Neural network recognition of optical images in special purpose sys-tems”, Collection of scientific works of the Military Institute of the T. Shevchenko, Issue 45, pp. 102-108.

Khoroshun, G., Luniakin, R., Riazantsev, A., Ryazantsev, O., Skurydina, T. and Tatarchenko, H. (2020), “The Development of an Application for Microparticle Counting Using a Neural Network”, Proc. of the 4th Int. Conf. on Computational Linguistics and Intelligent Systems (COLINS), Vol. I: Main Conference, pp. 1186-1195.

Ryazantsev, O., Khoroshun, G., Riazantsev, A., Ivanov, V. and Baturin, A. (2019), “Statistical Optical Image Analysis for Information System”, Proc. of 2019 7th Int. Conf. on Future Internet of Things and Cloud Workshops (FiCloudW), Istanbul, Turkey, IEEE 2019, pp. 130-134, DOI: https://doi.org/10.1109/FiCloudW.2019.00036.