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• ALGORITHM FOR PRE-PROCESSING VIDEO IMAGES TO INCREASE THE ACCURACY OF SMALL OBJECT DETECTION

  V.V. Kovalev, N.E. Sergeev

  2021-12-24

  Abstract ▼

  Recognition of certain patterns in video images captured by a camera is carried out using
  training methods based on convolutional neural networks. The larger the number of images with
  multiple features and the more diverse the training sample of video images, the better the convolutional
  neural networks extract features from the sequence of video images that were not included in
  the training sample. This is a consequence of increasing the accuracy of detecting visual images on
  video images containing features of target images. However, there are limitations in improving the
  detection performance when the size of the image to be detected is much smaller than the background
  area, or when the image is described with little information. To solve problems of this kind, the authors
  of the article have developed an algorithm for the spatio-temporal integration of information
  about the movement of dynamic images. The algorithm processes a fixed number of video images at
  certain points in time and extracts new independent signs of motion of dynamic images based on
  space-time processing of video images. Further, it combines new local motion features with the original
  video image features. This allows you to add a motion feature of dynamic images while preserving
  the original image features that describe static images. Areas of the video image that characterize
  the motion feature are displayed in a «color» cluster. The use of pre-processing is aimed at improving the accuracy of pattern detection, provided there are dynamic visual images on a static background.
  If the camera is in scan mode, a static background can be provided with a video stabilizer.
  Experimentally, estimates of integral criteria for the accuracy of detection neural network algorithms
  have been obtained, showing an increase in the accuracy of detecting visual images using
  the algorithm for spatial-temporal integration of motion information.

• WIRELESS SENSOR NETWORKS IN PROTECTED AREAS

  G.P. Vinogradov, A.S. Emtsev, I.S. Fedotov

  2021-04-04

  Abstract ▼

  For military purposes, wireless sensor networks allow you to "link autonomous systems" into a
  complex that has the property of self-organization, when objects "know" how to find each other and
  form a network, and in the event of a failure of any of the nodes can establish new routes for transmitting
  messages. It is possible to achieve the desired efficiency of such complexes, mainly by improving
  the intellectual component of their control system in general and individual node in particular.
  However, it should be noted that the vast majority of research in this area remains at the theoretical
  level. The goal is to: 1) the study and development of algorithms for network design with mobile
  nodes and their possible failures due to the combat mission; 2) the study and development of site use
  sensor network to collect, analyze, and transmit data about the situation and decision-making in the
  area of responsibility; 3) to offer relatively simple algorithms for giving the network node the property of intelligent behavior under the conditions of restrictions on power consumption and speed.
  It is shown that the required algorithms can be developed if the classes of typical situations and
  successful methods of action in real conditions are identified. On this basis, it becomes possible to
  develop formal models (patterns) for implementation in the node management system. A two-level
  structure of an intelligent network management system is proposed. The upper level, implemented
  by the operator, corresponds to such properties as survival, security, fulfillment of mission obligations,
  accumulation and adjustment of the knowledge base in the form of effective behavior patterns.
  The object of control for it is the network, considered as a functional system.

• DIRECTIONAL AND POLARISATION PROPERTIES OF A MICROSTRIP RECONFIGURABLE ANTENNA WITH TUNABLE FREQUENCY AND POLARISATION

  А. А. Vaganova, N.N. Kisel, A.I. Panychev

  2021-07-18

  Abstract ▼

  A reconfigurable antenna is an antenna with parameters that can be varied according to the
  requirements of a particular situation. Under variable parameters we can understand the operating
  frequency range, radiation pattern, polarization, as well as various combinations of these parameters.
  In this paper, we propose the design of a reconfigurable microstrip antenna with tunable
  frequency and polarization, and investigate its radiation pattern and polarisation properties. The
  antenna has compact dimensions and can be used in wireless communication systems operating in
  the 2–7 GHz range. 5 pin diodes are included into the antenna design to change the resonant frequency
  and polarization of the antenna by turning the diodes on and off. The simulation of the
  proposed antenna was performed in the FEKO program and the main parameters of the antenna
  were obtained. The analysis of the simulation results showed that for the lower part of the studied
  frequency range (2.05, 2.45 and 3.7 GHz), the polarization is linear. When operating in the higher
  sub-range (5.4, 5.6 and 5.75 GHz), the antenna is circularly polarized, and the direction of the
  polarisation vector rotation depends on the connection of the diodes. This ability to switch polarization
  to orthogonal at the same frequency allows to perform efficient signal reception in the conditions
  of multipath propagation.

• DEVELOPMENT OF A METHOD FOR PERSONAL IDENTIFICATION BASED ON THE PATTERN OF PALM VEINS

  V.А. Chastikova, S.А. Zherlitsyn

  2022-11-01

  Abstract ▼

  The article describes the work on the creation of a neural network method for identifying
  a person based on the mechanism of scanning and analyzing the pattern of palm veins as a biometric
  parameter. As part of the study, the prerequisites, goals and reasons for which the deve lopment
  of a reliable biometric identification system is an important and relevant area of activity
  are described. A number of problems are formulated that are inherent in existing methods for
  solving the problem: the graph method and the method based on calculating the distance expressed
  in various interval metrics. The description of the principles of their work is given.
  The tasks solved by personal identification systems are formulated: comparison of the subject of
  identification with its identifier, which uniquely identifies this subject in the information system.
  A mechanism for reading a pattern of veins from the palm of the hand, developed for analyzing
  an image obtained with a digital camera sensitive to infrared radiation, is described. When the
  palm is in the frame, illuminated by the light of the near infrared range, the image obtained
  from the camera becomes noticeable pattern of veins, vessels and capillaries that lie under the
  skin. Depending on the organization, the identification system may, based on the provided identifier,
  determine the appropriate access subject or verify that the same identifier belongs to the
  intended subject. Three methods for further analysis of biometric data and personal identification
  are given: approaches based on categorical classification and binary classification, as well
  as a combined approach, in which identification is first used by the first method, and then, by
  the second, but already for a known access identifier defined on the first stage. The resulting
  architecture of the neural network for the categorical classification of the vein pattern is pr esented,
  a method for calculating the number of model parameters depending on the number of
  registered subjects is described. The main conclusions and experimental measurements of the
  accuracy of the system when implementing various methods are presented, as well as diagrams of
  changes in the accuracy of models during training. The main advantages and disadvantages of the
  above methods are revealed.

• A SYSTEM FOR AUTOMATING DOCUMENT FLOW AND MONITORING ECONOMIC SECURITY INCIDENTS BASED ON ARTIFICIAL INTELLIGENCE TECHNOLOGIES

  А.Е. Anpilogova , V.А. Anpilogov

  31-41

  2025-07-24

  Abstract ▼

  Automation of document flow is a key element of process optimization and efficiency improvement. Automation of document flow based on artificial intelligence improves the management of economic security incidents by optimizing work processes and reducing costs. The transition to automated document flow in Russia is associated with a complex regulatory framework and large-scale implementation costs at  enterprises. Automation helps to comply with legal requirements and reduces the risks of legal and financial consequences. Integration of digital signatures increases the efficiency of document approval.
  The implementation of automation systems supports national digital transformation goals. Automation of document flow reduces dependence on paper processes and facilitates the creation of centralized digital repositories. The implementation of document automation systems requires a strategic approach and careful planning. Document automation provides time savings, reduced errors and increased compliance with regulatory standards. The article discusses the theoretical foundations of BPM, integration of digital technologies and regulatory aspects specific to Russia. The proposed system combines monitoring with AI and IoT, provides real-time data processing, automates the creation of legal documents and reports. The workflow automation system is based on data integration, artificial intelligence technologies and seamless solutions. The system combines monitoring technologies, facial recognition and behavior analysis algorithms, a centralized database and a communication module. The system generates reports and legal documents certified by QES and ensures interaction with law enforcement agencies and security services. Implementation results: a 30–40% reduction in operating costs and a 50% reduction in losses. The system complies with digital transformation standards and supports the modernization of the national economy.