ElAr :: Перегляд за автором "Kobylin, O."

Перегляд за автором "Kobylin, O."

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Application of deep learning methods for recognizing and classifying culinary dishes in images
(International Journal of Academic and Applied Research, 2023) Tvoroshenko, I.; Gorokhovatskyi, V.; Kobylin, O.; Tvoroshenko, A.
The paper deals with the actual tasks of computer vision – recognition and classification of objects in images. Deep learning methods based on neural networks are proposed as an alternative to existing methods. A new approach for effective recognition and classification of culinary dishes in images has been developed, which involves the use of the capabilities of the TensorFlow deep learning library and the features of the Convolutional Neural Network. A software application for recognizing and classifying culinary dishes has been developed. Testing of the proposed tool showed that 7 complete epochs of model training provided 77% accuracy, which is a fairly good result, given that one of the main problems in recognizing culinary dishes is interclass similarity. The prospect of further research is to create subclasses for existing general classes of dishes.
Application of video data classification models using convolutional neural networks
(International Journal of Academic and Applied Research, 2023) Tvoroshenko, I.; Pomazan, V.; Gorokhovatskyi, V.; Kobylin, O.
This paper explores the classification of video data with convolutional neural networks. It discusses how convolutional neural network architecture can do this task with fastness and maximum efficiency. By analyzing the different convolutional neural network models model was proposed that showed great results in this video classification task. The strengths and weaknesses of the neural network model for video classification have been identified, and the prospects for further work have also been outlined.
Comparison of standard image edge detection techniques and of method based on wavelet transform
(IJAR, 2014) Kobylin, O.; Lyashenko, V.
Image edge detection is in the forefront of image processing. There are lots of various edge detection methods. However the choice of a certain image edge detection technique still remains topical and this issue is constantly in focus for the researchers. This owes to both the specifics of implementing certain image edge detection technique and to the specifics of obtaining and presenting images for further processing. Based on this, in this paper, the comparison of standard image edge detection techniques (Canny, Prewitt, Robert, Sobel) and methods based on wavelet transform are studied. Quantitative measures for evaluating edge detection quality and simple visual comparison of the obtained edge maps of the original image are used for comparison. The advantages and disadvantages of these edge detection techniques have been shown.
Contour detection and allocation for cytological images using Wavelet analysis methodology
(ijarcsms, 2016) Lyashenko, V.; Matarneh, R.; Kobylin, O.; Putyatin, Y.
Image analysis is one of most powerful tools in various research fields. In the same context, processing of microscopic images in medicine has high priority research area, this is because such studies allow conducting comprehensive diagnosis of human health state, identifying and preventing the development of diseases in the early stages and providing additional research in non-standard symptomatic forms of rare diseases. To overcome analyzing and processing complexities of microscopic images the feasibility of using wavelet analysis methodology had been considered with a high attention to the effect of wavelet transform scaling which is used to detect contours of objects in the image. The new approach showed that the effectiveness of contour detection is largely depends on wavelet transform scaling to identify gaps in the wavelet decomposition of the investigated images.
Contrast Modification as a Tool to Study the Structure of Blood Components
(JECET, 2016) Lyashenko, V.; Matarneh, R.; Kobylin, O.
This paper focuses on the analysis and processing of blood microscopic images because of its importance to do a comprehensive analysis and diagnosis of human health. Due to the complexity of such work, we did explore various possible methods such as histogram equalization of brightness values (luminance), non-linear stretching of dynamic range of brightness values, masks filtering and fuzzy masking to get more accurate results. Color segmentation method has been used to analyze the structure of blood microscopic images. The results have showed that image segmentation increases when using fuzzy masking method, which in turn leads to increase and improve the analysis of blood microscopic images.
Digital Image Processing Techniques for Detection and Diagnosis of Fish Diseases
(IJARCSSE, 2016) Lyubchenko, V.; Matarneh, R.; Kobylin, O.; Lyashenko, V.
Image processing is used in many fields of knowledge because it allows the automate processes to get more information about the object being examined. One of directions of use of image processing technology is the study of fauna and flora, and in particular, the detection and diagnose of diseases of some representatives of fauna. In this article, we looked at the possibility of studying fish diseases by applying the methodology of color image segmentation. The surfaces of fish body considered the main information source to detectinfections. We successfully have detect infected areas on fish body and identified a total area of lesions.The proposed method makes it possible to automate the process and reduce the time of diagnosis of Infectious dangerous fish diseases.
Experiments with Fusion of Images with Use of Wavelet Transformation in Problems of the Text Information Analysis
(IJERGS, 2015) Lyashenko, V.; Mohammad, A.; Kobylin, O.
An analysis of images is the powerful tool of research in various fields of knowledge. One of directions of application of such analysis is a computer processing of text information. There is defined a number of problems among existing variety of methods of image processing of a text, where a wavelet procedure of fusion of images is in the basis. There is carried out a number of experiments for the purpose of a substantiation of possibility and expediency of application of wavelet procedure of fusion of images for the computer processing and the analysis of text information. As a result of the carried out experiments, a complexity of a choice of a fusion method of investigated images and an estimation of quality of such fusion are shown. Necessity of use of adaptive procedures is proved at a choice of a fusion method of approximating and detailing coefficients of wavelet expansion.
General Ideology of Analysis Digital Medical Images in RGB Format
(WARSE, 2020) Lyashenko, V.; Kobylin, O.; Ryazantsev, O.; Ryazantsev, I.; Barbaruk, V.; Zhychenko, Y.
Methods, technologies and various digital image processing procedures are one of the data analysis tools. At the same time, digital images can be considered as data that belong to the Big Data group. This fully applies to digital color images of cytological preparations. Thus, digital image processing techniques are one of the Big Data analysis tools. A feature of such a tool is the specificity of its use for various types of data, which are presented in the form of digital images. To do this, we examined the problematic aspects of the analysis of cytological specimens of images that are marked in the works of other authors. The paper also examined the issues of complex analysis of color images of cytological preparations. For this analysis, we used the decomposition of the original image into separate color channels, applied the ideology of wavelets to determine areas of interest and a set of morphological operations to specify such areas of interest. These methods are selected taking into account the peculiarities of images of cytological preparations. The results are shown on the example of images of cytological preparations, where megaloblastic anemia cells are also present.
General Methodology for Implementation of Image Normalization Procedure Using its Wavelet Transform
(IJSR, 2014) Lyashenko, V.; Kobylin, O.; Ahmad, M. Ayaz
Image processing is one of the fundamentals of various intelligence systems based on data analysis. In addition among the variety of different methods and approaches to image processing, image normalization methodology can be pointed out. The essence of such image processing methodology is in compensating various geometrical distortions of input image that was obtained through registering test image and forwarding it to the data mining system, in comparison with some reference (master) image. In such case, there arises a problem of time reduction for normalization procedure for some image processing systems. It is suggested that this task can be solved through the use of levels of wavelet decomposition of input image and conducting normalization procedure on separate levels. To solve this problem, this articles studies special aspects of wavelet decomposition of the image into separate levels of decomposition, functionality types of basic groups of image normalization by taking into account the use of wavelet decomposition levels of the test image, general methodology for determining transformation groups for image normalization based on wavelet decomposition. The fairness of the considered methodology is supported by the number of experiments.
Image Processing a New Era in the Study of Natural Polymer Composites
(ASIAN ACADEMIC RESEARCH ASSOCIATES, 2016) Lyashenko, V.; Mohammad, A.; Lyubchenko, V.; Kobylin, O.; Khan, A.
Image processing is one of the fundamentals of various intelligence systems based on data analysis. It is caused by that the significant part of information about outward things can be received on the basis of the video data analysis about images of the real world. As an example, we reviewed the methodology of image processing in the study of polymer compositions. We have shown the need to apply the methodology of image processing in the study of polymer compositions. Such analysis uses various methods, approaches and theories where the special place is occupied by the procedures connected with recognition of scenes or separate objects, presented on incoming images. This allows you to improve the study of the properties of fiber as a reinforcing agent in polymer compositions.
Methodology of Correlation Analysis in Solution of a Problem of Normalization of Projective Image Transformations
(IJSER, 2015) Lyashenko, V.; Mohammad, A.; Lyubchenko, V.; Kobylin, O.
Processing and interpretation of images is one of composing systems of the intellectual analysis of data. It is caused by that the significant part of information about outward things can be received on the basis of the video data analysis about images of the real world. At that, such analysis uses various methods, approaches and theories where the special place is occupied by the procedures connected with recognition of scenes or separate objects, presented on incoming images. Thus, it is necessary to consider the fact, that incoming images owing to objective factors could be subject to various geometrical distortions. Such distortions impose the restrictions and features on possibility of application of separate approaches and methods to processing and interpretation of images. Hence, a procedure of correlation normalization of images which allows to compare and recognize images is considered in this work. The work proves the possibility of representation of projective group of transformations, as one of versions of geometrical distortions of the incoming image, in the form of composition of the basic, simple transformations which are also versions of geometrical distortions of the incoming image. At the same time, the expediency of application of a partial correlation method for realization of procedure of correlation normalization of images is considered. The formalized description of the offered procedure of correlation normalization of images is given. Examples of separate steps of realization of the offered procedure are resulted.
On the construction of covering shapes for the analysis of economic dynamics
(The International Journal Research Publications Pte. Ltd., Singapore, 2014) Lyashenko, V.; Kobylin, O.
Getting more information from the available statistical data involves the use of different methods and approaches to the processing of such data. This is especially important from the point of view of weakly formalized processes, phenomena and objects, which include data on economic dynamics. At the same time an important element of extracting additional information about the studied processes, phenomena or objects is their visualization. This suggests the application feasibility of the visual analytics methodology, where the construction of covering figures on the set of points that describe processes, phenomena or objects of economic dynamics should be pointed out. Based on this, the paper suggests the procedure for the construction of the covering shape as a rectangle. Possible application methods for the proposed procedure in the analysis of economic dynamics tasks are described.
Processing Technique for Biomedical Image Analysis
(Severodonetsk, Ukraine, 2019) Lyashenko, V.; Kobylin, O.; Ryazantsev, O.; Ryazantsev, I.
Image processing methods are used in all areas of research. These methods provide additional information, a better understanding of the object that is being studied. Among the areas of using image processing methods, medicine occupies a special place. Biomedical data allow us to assess human health, to identify diseases in the early stages. Images of cellular structures of cytological preparations are one of the examples of biomedical data. Based on image analysis methods, we can isolate various components of cellular structures of cytological preparations. To do this, we apply the methods of wavelet analysis for different color components of the input image. Applying morphological analysis, we can identify individual cellular structures. The results are shown on the example of images of cellular structures of cytological preparations.
Research of superpixel image segmentation method
(2021) Kobylin, O.; Lysenko, A.
Study of Composite Materials for the Engineering using Wavelet Analysis and Image Processing Technology
(TJPRC, 2017) Lyashenko, V.; Mohammad, A.; Kobylin, O.; Khan, A.
Wavelet analysis and image processing technologies are important Tools for data analysis. We can apply these tools to the science of materials and polymers. This is important for the use of composite materials in engineering. We reviewed the methodology for wavelet analysis of image processing in the study of polymer compositions. We also use the contrasting procedure to improve the wavelet analysis. This allows you to improve the study of the properties of fiber as a reinforcing agent in polymer compositions for use in engineering. In this paper experiments had been held. The results presented here were found satisfactory and also are in good agreement with our earlier work and some other worker in the same field.
The Methodology of Image Processing in the Study of the Properties of Fiber as a Reinforcing Agent in Polymer Compositions
(IJARCS, 2016) Lyashenko, V.; Lyubchenko, V.; Mohammad, A.; Alveera, Khan; Kobylin, O.
Fillers added to the matrix material help to enhance the properties of a composite. We reviewed the methodology of image processing in the study of polymer compositions. We have shown the need to apply the methodology of image processing in the study of polymer compositions. This allows you to improve the study of the properties of fiber as a reinforcing agent in polymer compositions.
The methodology of wavelet analysis as a tool for cytology preparations image processing
(DergiPark, 2016) Babker, A.; Lyashenko, V.; Kobylin, O.
Purpose: The aim of this study was to determine the possibility of using wavelet analysis for processing images of cytology preparations. Material and Methods: A set of different images of cytology preparations were analyzed through changes in their contrast and application of the methodology of the wavelet analysis. Results: Developed procedure of processing of cytology preparations images. Procedure of processing of cytology preparations images allows to qualitatively (in terms of their visualization) allocating: cells’ edges, cell nuclei, revealing in more detail textural features of cells’ images, which allows analyzing cell structure. Conclusion: Consider the possibility and feasibility issues of applying wavelet analysis for processing cytology preparations images. This improves the quality of the analysis of cytology preparations images. This allows the to properly diagnose.
Time Series Clustering Based on the K-Means Algorithm
(Journal La Multiapp, 2020) Kobylin, O.; Lyashenko, V.
Time series is one of the forms of data presentation that is used in many studies. It is convenient, easy and informative. Clustering is one of the tasks of data processing. Thus, the most relevant currently are methods for clustering time series. Clustering time series data aims to create clusters with high similarity within a cluster and low similarity between clusters. This work is devoted to clustering time series. Various methods of time series clustering are considered. Examples are given for real data.
Using the methodology of wavelet analysis for processing images of cytology preparations
(MedSci Publications, 2016) Lyashenko, V.; Babker, A.; Kobylin, O.
Processing of microscope images in medicine is one of the priority research areas. This is due to the fact that such studies allow conducting comprehensive diagnosis of human health state, identifying and preventing the development of diseases in the early stages, providing additional research in non-standard symptomatic forms of rare diseases. In this connection, first of all image processing of cytology preparations holds a special place as one of the common set of microimages in medicine. However, the specific complexity of visualization process of cytology preparations and their subsequent processing with the use of automated processing determines the necessity to study new possibilities to use new approaches to image processing. Exactly this fact was the basis for considering the possibility to use wavelet analysis as a tool for processing cytology preparations images. On certain examples of cytology preparation images the results of application of one of the wavelet analysis procedures is shown.
Wavelet Analysis and Contrast Modification in the Study of Cell Structures Images
(WARSE, 2020) Lyashenko, V.; Kobylin, O.; Selevko, O.
Image processing is one of the data analysis tools. It is also a tool for getting more information. Such a tool occupies a special place for data research in the field of medicine. The imaging of cellular structures is an important example of medical data. The article describes the procedure for analyzing images of cellular structures. This procedure includes: changing the contrast of the image and using wavelet analysis to highlight the edges of objects in the image. Examples are given. The efficiency of the considered procedure is shown in comparison with classical methods.

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