The article examines a new method of detecting technical means that use a radio channel to transmit intercepted information. The method is based on the method of differential transformations and approximation of the spectral function in the basis of the transfer functions of the second order resonant units.To detect the signals of the secret means of obtaining information, it is proposed to determine at the first stage the spectrum of signals. The signals of the means of secretly obtaining information can be approximated by differential Taylor transformations, or more simply by T transformations. Moreover, differential images are differential T - spectra. Subsequently, an approximation of the already spectral function is performed in order to extract the components of the essential signal.In order to confirm the proposed technique, modeling of the exponential function was performed. The received graphic materials. Graphic materials fully confirm the reliability of the proposed method.

The new method for detecting signals of means of covert obtaining information

It was analyzed the main atmospheric factors effecting formation of optoelectronic images. It was done the analysis of the known methods of images segmentation received from the board of the optoelectronic surveillance systems. It has been established the basic disadvantages inherent of the classical images segmentation methods. It was suggested a swarm segmentation method of images obtained from on-board optoelectronic surveillance systems. As a method of segmentation, it was suggested to use the method of artificial bee colony. Experimental results on segmentation of the optoelectronic image were conducted by artificial bee colony method.

A Swarm Method for Segmentation of Images Obtained from On-Board Optoelectronic Surveillance Systems

New principles and approaches to evaluating the effectiveness of the targeting strategy are considered, based on a comparison of the quality of the decisions made by the company depending on specific tasks.

Effectiveness of Targeting Informational Technology Application

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Segmentation of optical-electronic images from on-board systems of remote sensing of the earth by the artificial bee colony method

This paper reports an improved method for processing the image of a vehicle's license plate when shooting with a smartphone camera. The method for processing the image of a vehicle's license plate includes the following stages:
– enter the source data; 
– split the video streaming into frames; 
– preliminary process the image of a vehicle's license plate;
– find the area of a vehicle's license plate;
– refine character recognition using the signature of a vehicle's license plate; 
– refine character recognition using the combined results from frames in the streaming video; 
– obtain the result of processing.
Experimental studies were conducted on the processing of images of a vehicle's license plate. During the experimental studies, the license plate of a military vehicle (Ukraine) was considered. The original image was the color image of a vehicle. The results of experimental studies are given. A comparison of the quality of character recognition in a license plate has been carried out. It was established that the improved method that uses the combined results from streaming video frames works out efficiently at the end of the sequence. The improved method that employs the combined results from streaming video frames operates with numerical probability vectors.
The assessment of errors of the first and second kind in processing the image of a license plate was carried out. The total accuracy of finding the area of a license plate by known method is 61 % while the improved method's result is 76 %. It has been established that the minimization of errors of the first kind is more important than reducing errors of the second kind. If a license plate is incorrectly identified, these results would certainly be discarded at the character recognition stage.

/pdf/devising-a-method-for-processing-the-image-of-a-vehicle-s-1ebjxerl.pdf

Devising a method for processing the image of a vehicle's license plate when shooting with a smartphone camera

This paper considers the improved method for segmenting complex structured images acquired from space observation systems based on the particle swarm algorithm. Unlike known ones, the method for segmenting complex structured images based on the particle swarm algorithm involves the following:
– highlighting brightness channels in the Red-Green-Blue color space;
– using a particle swarm method in the image in each channel of brightness of the RGB color space;
– image segmentation is reduced to calculating the objective function, moving speed, and a new location for each swarm particle in the image in each RGB color space brightness channel.
Experimental studies have been conducted on the segmentation of a complex structured image by a method based on the particle swarm algorithm. It was established that the improved segmentation method based on the particle swarm algorithm makes it possible to segment complex structured images acquired from space surveillance systems.
A comparison of the quality of segmenting a complex structured image was carried out. The comparative visual analysis of well-known and improved segmentation methods indicates the following:
– the improved segmentation method based on the particle swarm algorithm highlights more objects of interest (objects of military equipment);
– the well-known k-means method assigns some objects of interest (especially those partially covered with snow) to the snow cover (marked in blue);
– the improved segmentation method also associates some objects of interest that are almost completely covered with snow with the snow cover (marked in blue).
It has been established that the improved segmentation method based on the particle swarm algorithm reduces segmentation errors of the first kind by an average of 12 % and reduces segmentation errors of the second kind by an average of 8 %

/pdf/devising-a-method-for-segmenting-complex-structured-images-1u6sur4a.pdf

Devising a method for segmenting complex structured images acquired from space observation systems based on the particle swarm algorithm

It was done the analysis of the known methods of segmenting images which obtained from the board of the optoelectronic surveillance. It has been established the basic disadvantages inherent in the classical methods of the image segmentation with specific imaging in airborne optoelectronic observation. It was suggested at the segmentation of the optoelectronic images to conduct their multiple transformations previously. Gaussians was selected with the appropriate scale factor values as a core transformation. The using of the evolutionary method proposed in a method of the segmentation. Experimental study on segmentation of multiple sequence of the optoelectronic image were conducted by evolutionary method.

An improved method for segmentation of a multiscale sequence of optoelectronic images

The paper considers the proposals for improving of air surveillance informativity in small-base MIMO radar system based on two-dimensional radars. It is proposed the method of calculating the third coordinate (altitude) by means of increasing the informativity of the MIMO Radars system. This becomes possible as a result of the use of information contained in the structure of the electromagnetic field more efficient than in the monostatic two-coordinate radar. The calculations of the altitude measurement error of the multistatic radar system are carried out by the mathematical model method.

Hennadii Khudov

Papers

A Swarm Method for Segmentation of Images Obtained from On-Board Optoelectronic Surveillance Systems

Devising a method for processing the image of a vehicle's license plate when shooting with a smartphone camera

Devising a method for segmenting complex structured images acquired from space observation systems based on the particle swarm algorithm

An improved method for segmentation of a multiscale sequence of optoelectronic images

Proposals for Improving of Air Surveillance Informativity in MIMO Radar Systems Based on Two-Dimensional Radars