Methods and means research of identifying objects in video images
Students Name: Cherneha Volodymyr Vitaliiovych
Qualification Level: magister
Speciality: Computer Systems and Networks
Institute: Institute of Computer Technologies, Automation and Metrology
Mode of Study: full
Academic Year: 2020-2021 н.р.
Language of Defence: ukrainian
Abstract: Wavelet analysis is a possible tool for converting and making signals in the time part of the domain. The basis of its own functions, through which a large decomposition of signals, provides the use of special authorities and capabilities [2]. The functions of the introduced database allow to localize the features of the analyzed processes, which cannot be detected by traditional Fourier and Laplace transforms. Wavelet analysis theory provides a convenient and effective tool for solving many practical problems. The main area of application of wavelet transforms is the analysis and blocking of signals and functions that are non-stationary in time or inhomogeneous in space [5], when the results of the analysis can be created not only by common frequency characteristics of signals (distributed energy signals by frequent composition), but also information about certain local coordinates, by which certain groups of frequency compositions express themselves, or by means of which the frequency components of signals change rapidly [1]. Compared with the decomposition of signals on the Fourier series, wiles with much higher accuracy represent the local features of the signals, up to the breaks of the 1st kind (jumps) [4]. In contrast to the Fourier transform, wavelet transform of homogeneous signals through two-dimensional scanning [3], where frequency and coordination are considered as independent variables that allow to analyze signals in two spaces. Methods for identifying the spectral characteristics of signals using wavelet transform were proposed and studied by Barzynsky VP, Saukov AM, Bikova TV, Dudko PG, Kolodyazhny VV, Avrutova IV, Korepanov VV, Vorobyov V., Dremina IM, Kaiser G., J. Lim, M. Padma, C. Runshen and others. Ososkova G., Shitova AB, Stadnika A., S. Qian, T. Songu, and others made a significant contribution to the development of methods for designing and analyzing the material wavelet. Possibilities 8 of wavelet analysis in the problems of distribution of closely found signals described in the works of Shitov AB, Ilyina AA, V. Kumar, P. Addison. Despite many publications related to the practical application of wavelet transform, there is currently an unresolved line of execution related to the evaluation of the parameters of the wavelet transform in the study of objects of different nature: the choice of parameters in previous data on selection, selection wavelet -base, determining the level of wavelet decomposition, etc. Determining the optimal wavelet basis is a necessary step in wavelet analysis, because it is from this base that the processes of decomposition-assembly (decomposition and reconstruction) of signals will be carried out. When considering the method of application of the wavelet transform apparatus of leading domestic and foreign firms for the production of information technology data mining for the management of complex objects and systems, a number of problems were identified. One of the problems is the choice of material wavelet (wavelet basis) in the tested wavelet analysis, which is a separate task, but this choice is not fixed, is random and is due only to experience and various researchers. There is also no public approach to determining the optimal level of schedule for the separation of complex signals in independent warehouses. In addition, there remains an unresolved string of the set associated with determining the parameters of the wavelet transform itself. Aim and objectives of the study: The aim of the work is to increase the efficiency of analysis and diagnosis of objects of different nature by developing methods and information technology for a comprehensive evaluation of wavelet transform parameters. An object of research: the process of wavelet transformations of broadband signals The subject of research: algorithms and means of wavelet transformations of broadband signals. Research results : • analysis of existing methods of wavelet transform to solve problems of analysis and diagnosis of objects of different nature; • the method of construction of the wavelet-frequency characteristic is developed; 9 • the method of definition of effective wavelet basis at the performance of wavelet transformation is created; Thesis structure: The work consists of an introduction, five sections, conclusion, a list of references, and appendices. List of used literature sources: 1. Єгорова Є.В. Підсилювальні модулі передавачів систем зв’язку. //Праці 64- ї наукової сесії, присвяченій Дню радіо, Москва, 13-14 травня 2009 р. 2. Беликов И.Ю. Специализированное вычислительное устройство фонемной классификации речевых сигналов в реальном времени: дис. канд. техн. наук: 05.13.05 / И.Ю. Беликов. – Новочерскаск, 2013. – 159 с. 3. Подкур П.П. Масштабирующие функции и вейвлеты с коэффициентом масштабирования N>2: дис. канд. физ.-мат. наук: 05.13.18 / П.П. Подкур. – Кемерово, 2007. – 233 с. 4. Jaber A., Bicker R. Real-Time Wavelet Analysis of a Vibration Signal Based on Arduino-UNO and LabVIEW/ A. Jaber, R. Bicker // International Journal of Materials Science and Engineering, 2015. – Vol. 3, No. 1. – P. 66-70. 5. Астафьева Н.М. Вейвлет-анализ: основы теории и примеры применения //УФН. - 1996. - Т.166. - № 11. - С. 1145-1170