Determining the invariant of inter-frame processing for constructing the image similarity metric

Authors

DOI:

https://doi.org/10.15587/1729-4061.2023.276650

Keywords:

digital image, color atlas, geographic information object, ontology, measure, similarity, hash function, diffeomorphism, persistent homology

Abstract

The relevance of modeling digital images is determined by the need to implement approaches in the study of localization and identification of objects in order to reduce the amount of data. In this paper, the study object is the topology of a discrete two-dimensional image within the framework of the problem of determining the invariants of diffeomorphic transformations. Geographic information objects (GIOs) refer to objects that are on a given surface or objects that locally change the surface. With regard to objects, it is assumed that the change in their geolocation in the process of forming both single images and an extended series of frames obtained in the process of continuous monitoring is insignificant. In the process of scanning the surface, possible changes in the position of the image source are taken into account, for example, such as yawing, rolling, and pitch in the case of unmanned aerial vehicles (UAVs). These maneuvers are represented as a group of diffeomorphisms that are controlled by the internal gyroscopes of the carrier and the external navigation system. Based on the studies reported here, the initial ontology of digital images (ODI) has been determined by using the model of color spaces and functions of a special kind. The presence of an ontology makes it possible to build an adequate topology of color distribution in the image and take into account the specificity of the distribution of different colors in a digital image. The study results indicate that a promising method is to determine the similarity by constructing a color atlas structure graph (CASG) based on ODI and by determining invariants as a fragment of CASG inherited by all images in the sequence. The scope and conditions for the practical use of the result include its application to the analysis of images by methods of artificial intelligence

Author Biographies

Elena Gorda, Kyiv National University of Construction and Architecture

PhD, Associate Professor

Department of Information Technologies

Anatolii Serdiuk, Warsaw University of Technology

PhD, Associate Professor

Division of Automation and Aeronautical Systems

Ivan Nazarenko, Kyiv National University of Construction and Architecture

Doctor of Technical Sciences, Professor, Head of Department

Department of Machinery and Equipment of Technological Processes

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Determining the invariant of inter-frame processing for constructing the image similarity metric

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Published

2023-04-17

How to Cite

Gorda, E., Serdiuk, A., & Nazarenko, I. (2023). Determining the invariant of inter-frame processing for constructing the image similarity metric . Eastern-European Journal of Enterprise Technologies, 2(2 (122), 19–25. https://doi.org/10.15587/1729-4061.2023.276650

Issue

Vol. 2 No. 2 (122) (2023): Information technology. Industry control systems

Section

Information technology

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Copyright (c) 2023 Elena Gorda, Anatolii Serdiuk, Ivan Nazarenko

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