Computer Optics

528-534

Authors: Nalimov A.G., Kotlyar V.V.

A three-level spiral metalens in an amorphous silicon film is designed. The metalens relief consists of two subwavelength gratings with a 220-nm period (for 633 nm wavelength) and depths of 90 and 170 nm. The metalens forms a left-hand circular polarized optical vortex with topological charge 2 when illuminated by a linearly polarized plane wave. The intensity distribution at a distance of 633 nm is in the form of a subwavelength circle, whereas the longitudinal projection of the Pointing vector has negative values on the optical axis, meaning that a backward energy flow occurs. Two subwavelength gratings with different depth act as quarter-wave plates, transforming linearly polarized light into circularly polarized light with a phase delay of (lambda)/2. This metalens combines functionalities of three optical elements: a quarter-wave plate, a spiral phase plate, and a high-NA diffraction metalens (NA close to unity).

544-549

Authors: Greisukh G.I., Ezhov E.G., Antonov A.I.

Based on the presented results of the research of residual chromatism of two-lens components made of technologically advanced and commercially available optical materials that are transparent in the mid-IR range, it has been shown that such components are an effective tool for correcting chromatism of zoom lenses of this spectral range.

557-561

Authors: Gladkikh V.A.

A regular circular weakly guiding double clad optical fiber is considered. For a single-mode regime of the waveguide, an expression for estimating the proportion of the mode field power penetrating into the outer continuous cladding is obtained using a standard approach and a Gaussian model. It is shown that a simpler and more transparent result is obtained in the Gaussian model, which can be used in practical applications, in particular, when designing this type of waveguides with a minimal proportion of power penetrating into the outer shell.

567-576

Authors: Kirilenko M.S., Khonina S.N.

We performed a comparative numerical study of the conservation of properties of individual Laguerre-Gauss beams and their superpositions in a random environment. The simulation is based on the extended Huygens-Fresnel principle. Studies have shown that increasing the number of rings of Laguerre-Gauss modes with the same vortex order allows one to increase the ratio of the energy of the minimum informative coefficient to the energy of the maximum parasitic coefficient, which is important when detecting information encoded in the coefficients. In addition, an increase in the number of rings partially compensates for the stronger effect of random fluctuations on beams with high topological charges. Such a positive impact can be explained by the structural redundancy of multi-ring distributions (the vortex phase structure of the beam is repeated in each ring). A similar result was obtained for beams corresponding to a two-mode superposition. The best result on information preservation was obtained for the superposition with duplication of information in complex conjugate coefficients, and the best ratio of informative energy to parasitic one was obtained for beams with the largest area.

586-595

Authors: Lavrinov V.V., Lavrinova L.N.

The reconstruction of a wave front containing random phase distortions of the light field is considered. The reconstruction is performed by a Hartmann method based on the approximation of the wave function by Zernike polynomials using estimates of local slopes. The slope values depend on the algorithms by which they are determined. The number of slopes is proportional to the number of focal spots recorded in the plane of the receiving device, which varies depending not only on the raster dimension, but also on the parameters of turbulence, design features of the receiving devices, as well as being restricted by the orthogonality of Zernike polynomials. Results of numerical experiments are given, which will be taken into account when creating adaptive optics systems for correcting strong turbulent distortions of the optical radiation.

605-610

Authors: Reznik A.L., Tuzikov A.V., Soloviev A.A., Torgov A.V., Kovalev V.A.

The article describes methods and algorithms related to the analysis of dynamically changing discrete random fields. Time-optimal strategies for the localization of pulsed-point sources having a random spatial distribution and indicating themselves by generating instant delta pulses at random times are proposed. An optimal strategy is a procedure that has a minimum (statistically) average localization time. The search is performed in accordance with the requirements for localization accuracy and is carried out by a system with one or several receiving devices. Along with the predetermined accuracy of localization of a random pulsed-point source, a significant complicating factor of the formulated problem is that the choice of the optimal search procedure is not limited to one-step algorithms that end at the moment of first pulse generation. Moreover, the article shows that even with relatively low requirements for localization accuracy, the time-optimal procedure consists of several steps, and the transition from one step to another occurs at the time of registration of the next pulse by the receiving system. In this case, the situation is acceptable when during the process of optimal search some of the generated pulses are not fixed by the receiving system. The parameters of the optimal search depending on the number of receiving devices and the required accuracy of localization are calculated and described in the paper.

618-626

Authors: Nikitin M.Yu., Konushin V.S., Konushin A.S.

Modern biometric systems based on face recognition demonstrate high recognition quality, but they are vulnerable to face presentation attacks, such as photo or replay attack. Existing face anti-spoofing methods are mostly based on texture analysis and due to lack of training data either use hand-crafted features or fine-tuned pretrained deep models. In this paper we present a novel CNN-based approach for face anti-spoofing, based on joint analysis of the presence of a spoofing medium and eye blinking. For training our classifiers we propose the procedure of synthetic data generation which allows us to train powerful deep models from scratch. Experimental analysis on the challenging datasets (CASIA-FASD, NUUA Imposter) shows that our method can obtain state-of-the-art results.

632-646

Authors: Mousavi S .M .H., Lyashenko V., Prasath V.B.S.

Edge detection is very important technique to reveal significant areas in the digital image, which could aids the feature extraction techniques. In fact it is possible to remove un-necessary parts from image, using edge detection. A lot of edge detection techniques has been made already, but we propose a robust evolutionary based system to extract the vital parts of the image. System is based on a lot of pre and post-processing techniques such as filters and morphological operations, and applying modified Ant Colony Optimization edge detection method to the image. The main goal is to test the system on different color spaces, and calculate the system’s performance. Another novel aspect of the research is using depth images along with color ones, which depth data is acquired by Kinect V.2 in validation part, to understand edge detection concept better in depth data. System is going to be tested with 10 benchmark test images for color and 5 images for depth format, and validate using 7 Image Quality Assessment factors such as Peak Signal-to-Noise Ratio, Mean Squared Error, Structural Similarity and more (mostly related to edges) for prove, in different color spaces and compared with other famous edge detection methods in same condition. Also for evaluating the robustness of the system, some types of noises such as Gaussian, Salt and pepper, Poisson and Speckle are added to images, to shows proposed system power in any condition. The goal is reaching to best edges possible and to do this, more computation is needed, which increases run time computation just a bit more. But with today’s systems this time is decreased to minimum, which is worth it to make such a system. Acquired results are so promising and satisfactory in compare with other methods available in validation section of the paper.

653-660

Authors: Gashnikov M.V.

Adaptive multidimensional signal interpolators are developed. These interpolators take into account the presence and direction of boundaries of flat signal regions in each local neighborhood based on the automatic selection of the interpolating function for each signal sample. The selection of the interpolating function is performed by a parameterized rule, which is optimized in a parametric lower dimensional space. The dimension reduction is performed using rank filtering of local differences in the neighborhood of each signal sample. The interpolating functions of adaptive interpolators are written for the multidimensional, three-dimensional and two-dimensional cases. The use of adaptive interpolators in the problem of compression of multidimensional signals is also considered. Results of an experimental study of adaptive interpolators for real multidimensional signals of various types are presented.

671-676

Authors: Morunov N.D., Golovashkin D.L.

The paper is devoted to the investigation of the implementation features of a block algorithm for the FDTD-method on GPU. The block algorithm in general and in the context of the FDTD-method in particular is discussed. The main attention is paid to specifics of determining the shape and volume of blocks, which stem from the use of MATLAB and its Parallel Computing Toolbox. The practical efficiency of the proposed techniques is shown. Possible applications and prospects are discussed.

692-698

Authors: Zhirnov A.A., Kudrjashova O.B.

This study is focused on enhancing the informativity of optical measurement techniques for particulate matter. The problem is that the description of particulate matter with bimodal and multimodal distributions by an a priori defined analytical function of particle size distribution (for example, a log-normal distribution) is not accurate enough. Here, we explore if experimental data can be approximated by a multivariable function of particle size distribution instead of using the a priori defined log-normal distribution. For the comparison of the approximation results, experiments are conducted on standard samples with granulometric compositions OGS-01LM and OGS-08LM separately and jointly in a mix. The experimental data are recorded by a high-selectivity turbidimetric technique in water suspensions of these samples. The purpose of this study is to present the measurement results as a distribution function that enables one to identify more accurately the particle-size distribution profile and the corresponding disperse characteristics of the aerosol in question when measuring parameters of disperse media by optical techniques. The main objective of this work is to develop, implement and verify a search algorithm for the particle-size distribution function by way of a multi-parameter function. We show that the solution to the problem proposed herein is more universal because it allows slow and fast processes in suspensions and aerosols to be examined with a lower error. The algorithm can be applied to the problems which are based on solving first-kind Fredholm equations.