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Telecommunications and Radio Engineering

Published 12 issues per year

ISSN Print: 0040-2508

ISSN Online: 1943-6009

SJR: 0.185 SNIP: 0.268 CiteScore™:: 1.5 H-Index: 22

Indexed in

USING FUZZY CLUSTERING IN STRUCTURAL METHODS OF IMAGE CLASSIFICATION

Volume 79, Issue 9, 2020, pp. 781-791
DOI: 10.1615/TelecomRadEng.v79.i9.50
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ABSTRACT

The results of image classification problem solving using structural methods in computer vision systems are presented. The technology for introducing fuzzy clustering on a set of descriptors of keypoints for a dataset of image etalons has been developed. The usage of membership function values obtained by the results of fuzzy clustering is proposed, which makes it possible to calculate individual numerical characteristics for classification of the images being recognized. Mathematical and software classification models for data analysis based on the values of structural descriptions are developed, the properties and features of the usage of these models are investigated, and the effectiveness based on the results of processing specific images is evaluated. The classification efficiency using calculated weights for the descriptor system has been experimentally confirmed. Based on the research, it was concluded that classification technologies based on the fuzzy characteristics of etalon data are effective for compression of the space of structural features and reducing computational costs.

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CITED BY
  1. Daradkeh Yousef Ibrahim, Tvoroshenko Iryna, Gorokhovatskyi Volodymyr, Latiff Liza Abdul, Ahmad Norulhusna, Development of Effective Methods for Structural Image Recognition Using the Principles of Data Granulation and Apparatus of Fuzzy Logic, IEEE Access, 9, 2021. Crossref

  2. Wang Chunyan, Wang Xiang, Wu Danfeng, Kuang Minchi, Li Zhengtong, Meticulous Land Cover Classification of High-Resolution Images Based on Interval Type-2 Fuzzy Neural Network with Gaussian Regression Model, Remote Sensing, 14, 15, 2022. Crossref

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