D.M. Murashov
Federal Research Center "Computer Science and Control", Russian Academy of Sciences, Moscow, Russia
Keywords: image segmentation, image partition, combining segmentation maps, measure of information redundancy, variation of information
In this paper, we propose a new two-level method for combining image segmentation maps based on minimizing the two-objective quality functional. The functional is formed as a weighted sum of the information redundancy measure and variation of information computed from the original image and the combined segmentation map. Applying such a measure, we obtain an image partition that provides a compromise between the objectives of minimizing the number of outlined informationally important segments and minimizing the information difference between the original image and the resulting partition. The proposed method improves the result of segmentation in comparison with the method for combining partitions based on the criterion of the minimum information redundancy.
N. A. Andriyanov1, K. K. Vasiliev2, V. E. Dementiev2, A. V. Belyanchikov2 1Financial University under the Government of the Russian Federation, Moscow, Russia 2Ulyanovsk State Technical University, Ulyanovsk, Russia
Keywords: image processing, doubly stochastic models, nonlinear filtering, image recovery
The article deals with the issues of image restoration when only a part of observations subjected to additive noise regularly placed in the original image is available. In other words, the problem of restoration of a thinned image is solved (based on pilot pixels). Pixels themselves are mixed with the white Gaussian noise. To solve this problem, special modifications of nonlinear filters are synthesized based on deep doubly stochastic Gaussian models. The results obtained allow us to draw a conclusion about the effectiveness of the proposed filters in comparison with linear methods and traditional algorithms. The study shows that images can be reconstructed based on only 50% of information using a doubly stochastic model, resulting in a relative error of only 9%.
A. G. Tashlinskii, R.O. Kovalenko
Ulyanovsk State Technical University, Ulyanovsk, Russia
Keywords: simulation, interpolation, target function, similarity measures, spatial deformations of images
A technique for eliminating the influence of the image interpolation effect in the algorithm of estimating image spatial deformations is proposed. The technique is considered for similarity measures of images used in the synthesis of algorithms, in particular, the mean square of the inter-frame difference, the inter-frame correlation coefficient, and the Shannon mutual information. Calculated expressions for compensating the influence of bilinear and bicubic interpolation are obtained. The developed technique is also applicable to other similarity measures used in the development of algorithms for estimating spatial deformations of images, as well as any interpolations: spline, using Lagrange and Newton polynomials, power functions, etc.
V.A. Fursov
Image Processing Systems Institute, Russian Academy of Sciences, Federal State Research Center "Crystallography and Photonics", Russian Academy of Sciences, Samara, Russia
Keywords: digital processing of images, defocusing, IIR filter, stability
The technology of constructing a recursive filter on a non-uniform grid of samples with parameter identification on test images is discussed. This filter is the IIR-filter that has a physical feasibility problem. To overcome it, a multi-step procedure is implemented. Unfortunately, identifying the best filter in terms of a given criterion does not guarantee that a recursive implementation of that filter will be stable. In the paper, for the considered iterative scheme, stability conditions are obtained. It has been experimentally confirmed that if, these conditions are met, it is possible to achieve a high quality of the correction. Based on the obtained criteria, a technology for correcting defocusing with control over the stability of estimates is proposed. The results of image correction showing the effectiveness of the technology are presented.
A.V. Karpov1, V.I. Kozik2, E.S. Nejevenko2, Y.Sh. Schwartz1 1Federal State Budgetary Institution "Novosibirsk TB Research Institute", Ministry of Health of the Russian Federation, Novosibirsk, Russia 2Institute of Automation and Electrometry, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia
Keywords: tuberculosis, x-ray picture, convolutional neural networks, diagnosis, training sets
The article explores the reliability of training samples used to train convolutional neural networks for the diagnosis of pulmonary diseases. It is shown that the sample, in which 3500 X-ray pictures of healthy patients and the same number of pictures of patients with tuberculosis, is very heterogeneous. When training on different parts of the sample and recognizing its various parts, significantly different results are obtained.
M. V. Gashnikov, M. A. Chubar, M. A. Yakubenko
Samara National Research University, Samara, Russia
Keywords: digital images, approximation, autoencoders, convolutional neural networks, adversarial neural networks
An image compression technology based on machine learning is developed. Segmentation of the original image into discarded and stored zones is applied. An algorithm of compression of stored zones based on the nested coverage of the image is used. Discarded zones are replaced by a reliable fake during decompression. Machine-learning algorithms based on autoencoders, convolutional and adversarial neural networks are used at all stages of compression technology (segmentation, pixel approximation of stored zones, fake of discarded zones, etc.). Computational experiments are performed to study the proposed compression technology and the included machine learning algorithms in natural images. The results of computational experiments confirm the prospects of the proposed technology for problems related to digital image compression.
A two-stage method for adaptive traffic signal control based on an estimate of the predicted weighted traffic flow passing through an intersection is proposed. At the first stage, we estimate the travel time required for each vehicle to pass the intersection using an artificial neural network model and estimate the predicted traffic flow through the intersection for a given phase of the traffic signal cycle. At the second step, a weighted flow estimate is formed, which takes into account the waiting time of vehicles. The proposed method for choosing the traffic signal phase is based on maximizing the weighted traffic flow. The results of experimental studies allow us to conclude that the proposed approach outperforms the classical approaches and state-of-the-art methods of traffic signal control based on reinforcement learning.
V. Minin Oleg1,2, V. Minin Igor1,2, Zhou Song3 1Tomsk Polytechnic University, Tomsk, Russia 2Siberian State University of Geosystems and Technologies, Novosibirsk, Russia 3Huaiyin Institute of Technology, Huai'an, China
Keywords: high-order Fano resonance, superresonance, extreme high electromagnetic fields, subwave localization of the field
The results of numerical simulation based on the Mie theory of the superresonance effect for a dielectric sphere with a low refractive index are presented. Water is used as a material of the mesoscale sphere. It is shown that not only the previously studied weakly dissipative mesoscale spheres made of a material with a “medium” (about 1.5) and high (more than 2) refractive index, but also a low one (about 1.3) support the high-order Fano resonance effect associated with internal Mie modes. In this case, the intensities of resonant peaks for both magnetic and electric fields in the vicinity of the poles of the sphere can reach extremely high values of the order of 106-107 for a water droplet with a Mie size parameter of about 70.
S.D. Poletayev
Image Processing Systems Institute, Russian Academy of Sciences, Federal State Research Center "Crystallography and Photonics", Russian Academy of Sciences, Samara, Russia
Keywords: COMSOL modeling, thin films, laser ablation, diffraction grating, resolution
The effect of changes in the thermophysical properties of the molybdenum film during intermediate oxidation during laser ablation on the dimensional effect of track formation is investigated by numerical simulation. In accordance with the data obtained, the hypothesis explaining the reduction of the track width in the ablation zone of the film in comparison with the effective diameter of the laser beam is refined. It is shown that a specific change in the thermal conductivity coefficient of a substance at the time of oxidation has a significant effect on the distribution of the temperature field, expressed in narrowing of the characteristic of the temperature distribution over the film surface, which has not been previously considered. It is established that the change in the density, specific heat capacity, and thermal effect of the chemical reaction of molybdenum oxidation during film oxidation does not significantly affect the temperature distribution in the zone of exposure to the laser beam.
Yu. V. Chugui
Technological Design Institute of Scientific Instrument Engineering, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia
Keywords: Fresnel and Fraunhofer diffraction, Fourier optics, diffractional Fraunhofer spectra of extended objects, volumetric slit hole, optical dimensional inspection
The features of formation of face images of extended absolutely slit objects with an arbitrary opening of holes are studied in a coherent-optical system. On the base of the constructive approximation of the spectra of spatial frequencies (Fraunhofer diffractional patterns) of objects with different dimensions of front and back apertures, formulas for the field in the image of the front face are obtained and analyzed. Cases of objects with significantly expanding and significantly narrowing apertures of an extended hole (the differences in aperture sizes are much larger than the size of the Fresnel zone) are investigated in detail. It is found that the image structure of faces depends on the type of the opening. With a positive opening, where the back face is in the shadow region, the field at the output of the system corresponds to the image of the front face; with a negative opening, the image of the back face is observed. It is shown that error of determination of boundaries in the image of the active face of the object is inversely proportional to the square of the aperture difference. The invariant properties of the projection system for forming images of external faces of extended holes with an arbitrary opening are analyzed.