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Development of effective methods for structural image recognition using the principles of data granulation and apparatus of fuzzy logic

The processes of intelligent data processing in computer vision systems have been researched. The problem of structural image recognition is relevant. This is a promising way to assess the degree of similarity of objects. This approach provides the simplicity of construction and the high reliability...

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Main Authors:	Daradkeh, Yousef Ibrahim, Tvoroshenko, Iryna, Gorokhovatskyi, Volodymyr, Abdul Latiff, Liza, Ahmad, Norulhusna
Format:	Article
Language:	English
Published:	Institute of Electrical and Electronics Engineers Inc. 2021
Subjects:	T Technology (General)
Online Access:	http://eprints.utm.my/id/eprint/94640/1/LizaAbdulLatiff2021_DevelopmentofEffectiveMethodsforStructuralImage.pdf http://eprints.utm.my/id/eprint/94640/ http://dx.doi.org/10.1109/ACCESS.2021.3051625
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spelling	my.utm.946402022-03-31T15:51:45Z http://eprints.utm.my/id/eprint/94640/ Development of effective methods for structural image recognition using the principles of data granulation and apparatus of fuzzy logic Daradkeh, Yousef Ibrahim Tvoroshenko, Iryna Gorokhovatskyi, Volodymyr Abdul Latiff, Liza Ahmad, Norulhusna T Technology (General) The processes of intelligent data processing in computer vision systems have been researched. The problem of structural image recognition is relevant. This is a promising way to assess the degree of similarity of objects. This approach provides the simplicity of construction and the high reliability of decision making. The main problem of an effective description of characteristic features is the distortion of fragments of analyzed objects. The reasons for changing the input data can be the actions of geometric transformations, the influence of background or interference. The elements of false objects with similar characteristics are formed. The problem of ensuring high-quality recognition requires the implementation of effective means of image processing. Methods of statistical modeling, granulation of data and fuzzy sets, detection and comparison of keypoints on the image, classification and clustering of data, and simulation modelling are used in this research. The implementation of the proposed approaches provides the formation of a concise description of features or a vector representation of unique keypoints. The verification of theoretical foundations and evaluation of the effectiveness of the proposed data processing methods for real image bases is performed using the OpenCV library. The applied significance of the work is substantiated according to the criterion of data processing time without reducing the characteristics of reliability and interference immunity. The developed methods allow to increase the structural recognition of images by several times. Perspectives of research may involve identifying the optimal number of keypoints of the base set. Institute of Electrical and Electronics Engineers Inc. 2021 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/94640/1/LizaAbdulLatiff2021_DevelopmentofEffectiveMethodsforStructuralImage.pdf Daradkeh, Yousef Ibrahim and Tvoroshenko, Iryna and Gorokhovatskyi, Volodymyr and Abdul Latiff, Liza and Ahmad, Norulhusna (2021) Development of effective methods for structural image recognition using the principles of data granulation and apparatus of fuzzy logic. IEEE Access, 9 . pp. 13417-13428. ISSN 2169-3536 http://dx.doi.org/10.1109/ACCESS.2021.3051625
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Daradkeh, Yousef Ibrahim Tvoroshenko, Iryna Gorokhovatskyi, Volodymyr Abdul Latiff, Liza Ahmad, Norulhusna Development of effective methods for structural image recognition using the principles of data granulation and apparatus of fuzzy logic
description	The processes of intelligent data processing in computer vision systems have been researched. The problem of structural image recognition is relevant. This is a promising way to assess the degree of similarity of objects. This approach provides the simplicity of construction and the high reliability of decision making. The main problem of an effective description of characteristic features is the distortion of fragments of analyzed objects. The reasons for changing the input data can be the actions of geometric transformations, the influence of background or interference. The elements of false objects with similar characteristics are formed. The problem of ensuring high-quality recognition requires the implementation of effective means of image processing. Methods of statistical modeling, granulation of data and fuzzy sets, detection and comparison of keypoints on the image, classification and clustering of data, and simulation modelling are used in this research. The implementation of the proposed approaches provides the formation of a concise description of features or a vector representation of unique keypoints. The verification of theoretical foundations and evaluation of the effectiveness of the proposed data processing methods for real image bases is performed using the OpenCV library. The applied significance of the work is substantiated according to the criterion of data processing time without reducing the characteristics of reliability and interference immunity. The developed methods allow to increase the structural recognition of images by several times. Perspectives of research may involve identifying the optimal number of keypoints of the base set.
format	Article
author	Daradkeh, Yousef Ibrahim Tvoroshenko, Iryna Gorokhovatskyi, Volodymyr Abdul Latiff, Liza Ahmad, Norulhusna
author_facet	Daradkeh, Yousef Ibrahim Tvoroshenko, Iryna Gorokhovatskyi, Volodymyr Abdul Latiff, Liza Ahmad, Norulhusna
author_sort	Daradkeh, Yousef Ibrahim
title	Development of effective methods for structural image recognition using the principles of data granulation and apparatus of fuzzy logic
title_short	Development of effective methods for structural image recognition using the principles of data granulation and apparatus of fuzzy logic
title_full	Development of effective methods for structural image recognition using the principles of data granulation and apparatus of fuzzy logic
title_fullStr	Development of effective methods for structural image recognition using the principles of data granulation and apparatus of fuzzy logic
title_full_unstemmed	Development of effective methods for structural image recognition using the principles of data granulation and apparatus of fuzzy logic
title_sort	development of effective methods for structural image recognition using the principles of data granulation and apparatus of fuzzy logic
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2021
url	http://eprints.utm.my/id/eprint/94640/1/LizaAbdulLatiff2021_DevelopmentofEffectiveMethodsforStructuralImage.pdf http://eprints.utm.my/id/eprint/94640/ http://dx.doi.org/10.1109/ACCESS.2021.3051625
_version_	1729703200663011328
score	13.211869

Development of effective methods for structural image recognition using the principles of data granulation and apparatus of fuzzy logic

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