Search

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Eastern-European Journal of Enterprise Technologies is the property of PC TECHNOLOGY CENTER and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The integrity of the information content, in particular the digital image considered in the work, is one of the criteria for its security. Image splicing is one of the most common methods of forgery today. This way of breaking the integrity of the image is easily implemented with the help of modern graphic editors (PhotoShop, Gimp, etc.). During image splicing, one image is created from several. The task of detecting image splicing is the subject of research by scientists in the field of information security around the world, but it remains relevant today: there are no universal expert methods that can even detect the presence of a "foreign" part in any case of image splicing; the effectiveness of existing methods needs to be increased even in limited conditions of their application. The paper presents a new polynomial degree 2 expert method, which makes it possible to separate the original image from one whose integrity is violated. The method is based on the analysis of the properties of the blocks smallest singular values matrix, which corresponds to the matrix of the digital image. The method localizes the area containing the part of another image. The developed method is based on established differences in the properties of the blocks smallest singular values matrix for digital images in different formats - lossy and lossless. These differences are reflected in the additional method of separating images in different formats proposed in the work. This method can be used both alone and as a component of the developed image splicing detection method in the case where the falsified image consists of parts of images stored with loss and without loss. It was established that the proposed expert method provides an increase in the efficiency of image splicing detection in comparison with the modern analogue method. [ABSTRACT FROM AUTHOR]

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Video analysis is a very important tool in video surveillance systems with one or more cameras. Among the most promising features are tracking the movement of objects - tracking. The current state of development in the field of tracking is considered in the work. There are several types of trekking. Pixel Tracking is the tracking of the movement of a specific point (pixel) or group of points on the original video sequence. The result of this process is the trajectory of the pixel, corresponding to the movement of an object in the frame. Matchmoving is a complex process that allows you to create a three-dimensional scene with a digital camera based on the available video sequence, which exactly repeats the movement of a real camera. Motion Capture is a technology designed to determine the position and orientation of a real object in a virtual environment, determining the position and orientation of a real object in space is carried out using special sensors and markers. Each of these types of tracking can be used on its own or as part of more complex processes. The paper develops a modification of the camera motion detection algorithm, which works in the field of Pixel Tracking. The description of the main approaches to motion estimation is given, namely recursive raster algorithms, frequency domain algorithms, optical flow algorithms and block matching methods. The urgency of the work, its purpose and objectives are given. The paper describes a method of arranging blocks in a video sequence frame, which are used to calculate the movement of the camera. Similarity metrics are used to estimate the similarity of the blocks, namely the correlation coefficient. The paper describes the steps of the developed modification of the camera motion detection algorithm. The results of the modification of the camera motion detection algorithm are presented. The result of this work is an indicator of the visual quality of tracking in the form of a 2D image of the camera motion vector. [ABSTRACT FROM AUTHOR]

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ukrainian Scientific Journal of Information Security is the property of National Aviation University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cloning remains one of the most common tools used for unauthorized changes to digital images. Cloning is implemented in all modern graphic editors. Many experts in the field of information security are engaged in solving the problem of cloning detection, but this task has no final solution to date. A modification of the method for identifying cloning results in a digital image is proposed in the paper. The effectiveness of this method exceeds the efficiency of modern analogues. It remains effective when the cloned image is subjected to additional disturbing influences. These disturbing influences do not differ for the clone and prototype. Also, the method is effective when the size of the clone / prototype is small. The purpose of the modification of the method is to ensure its effectiveness under the conditions of certain geometric transformations to which the clone is subjected. These transformations are: reflection relative to the vertical and/or horizontal axis, rotation through an angle multiple of 90°, reflection relative to the diagonal (main, secondary) of the corresponding matrix. In this paper, the principle of constructing a matrix of minimal block differences is changing. This matrix is mapped to a digital image. It is the main subject of research in the method. The element of the matrix of minimal block differences reflects the smallest difference of a particular block from any other block of the image. The difference between the blocks is calculated as the difference of their singular spectra. The singular spectrum of the matrix does not change during the geometric transformation. Advanced method has high efficiency. A value of TRP = 100 % indicates that when the method is running, skip-ping of cloned images does not occur. The improved method is also effective in identifying several clones that correspond to one prototype. Several clones experience different geometric transfor-mations.

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose. To develop an automated method based on machine learning for accurate detection of features of a damaged building on digital imagery. Methodology. This article presents an approach that employs a combination of unsupervised machine learning techniques, specifically Principal Component Analysis (PCA), K-means clustering, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), to identify building damage resulting from military conflicts. The PCA method is utilized to identify principal vectors representing the directions of maximum variance in the data. Subsequently, the K-means method is applied to cluster the feature vector space, with the predefined number of clusters reflecting the number of principal vectors. Each cluster represents a group of similar blocks of image differences, which helps to identify significant features associated with fractures. Finally, the DBSCAN method is employed to identify areas where points with similar characteristics are located. Subsequently, a binary fracture mask is generated, with pixels exceeding the threshold being identified as fractures. Findings. The introduced methodology attains an accuracy rate of 98.13 %, surpassing the performance of conventional methods such as DBSCAN, PCA, and K-means. Furthermore, the method exhibits a recall of 82.38 %, signifying its ability to effectively detect a substantial proportion of positive examples. Precision of 58.54 % underscores the methodology’s capability to minimize false positives. The F1 Score of 70.90 % demonstrates a well-balanced performance between precision and recall. Originality. DBSCAN, PCA and K-means methods have been further developed in the context of automated detection of building destruction in aerospace images. This allows us to significantly increase the accuracy and efficiency of monitoring territories, including those affected by the consequences of military aggression. Practical value. The results obtained can be used to improve automated monitoring systems for urban development and can also serve as the basis for the development of effective strategies for the restoration and reconstruction of damaged infrastructure. [ABSTRACT FROM AUTHOR]

In this paper it is proposed basics of a new approach to identify cloning results, conducted in digital images, in additional disturbing influences conditions in a digital image after cloning, that may be considered as lossy compression, add noise, blur, etc. The approach is based on identifying the comparability of the surface parts, which is put into correspondence the analyzed image appropriate clones and its preimage. The surface is determined by the graph of the interpolation spline, approaching the function of the image, and the elements of the image are regarded as the interpolation nodes. It is proved that as the main quantitative characteristics of such comparability is advisable to use the volume of a cylindrical body with generator parallel to the axis OZ, bounded from above corresponding part of the interpolation function graph, bounded below - plane XOY. [ABSTRACT FROM AUTHOR]

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article describes the computational method for segmenting smoothed objects images on digital images is developed. To reduce computational costs the segmentation is carried out only in areas extracted by the computational method of single objects images segmentation on digital images. Segmentation of smoothed images is carried out sequentially in each selected segment. To reduce computational costs only segments that contain more than one peak are analyzed. Such segments may contain either fragments of smoothed image, or a statistically dependent image of a compact group of objects. In this regard, the decision about the segmented image type is made based by the difference between the segmentation results of both types of object images: smoothed image and an image of a compact group. As a sign of distinguishing between smoothed image and an image of a compact group the ratio between the number of pixels assigned to the image of a compact group and the smoothed image segmented with the start pixel in one peak is used. Images of objects with non-zero visible motion during the exposure time become smoothed with their own motion and have an image whose shape is stretched along the direction of its apparent movement. At the same time, single objects as well as compact groups of objects are immovable during the exposure time. The form of such images of compact groups of objects is often close to circular. To decide the extent of the segmented image it is proposed to use the degree of elongation of its image on a digital frame. As an indication of the degree of elongation of the object image the estimate of the eccentricity value is used in the paper. A study of the developed method of smoothed images segmentation on digital astronomical images was carried out on digital frames obtained using telescopes from 8 astronomical observatories. The developed computational method allowed making a preliminary decision about the type of segmented image (smoothed image or image of a compact group) directly at the segmentation stage. The developed method of segmentation of smoothed images is applied in the software package for automated detection of asteroids and comets CoLiTec. With the use of the developed method, the segmentation of images of comets, asteroids, NEOs, artificial earth satellites is carried out. When processing digital frames obtained without using the daily reference mechanism, the developed method is used to select all objects in the digital image.

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)