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Telecommunications and Radio Engineering
SJR: 0.202 SNIP: 0.2 CiteScore™: 0.23

ISSN Imprimir: 0040-2508
ISSN En Línea: 1943-6009

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Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v75.i2.50
pages 155-168

INTELLECTUAL DATA PROCESSING AND SELF-ORGANIZATION OF STRUCTURAL FEATURES AT RECOGNITION OF VISUAL OBJECTS

V. A. Gorokhovatskiy
Kharkiv Educational and Scientific Institute of State Higher Educational Institution (SHEI) "Banking University" Kharkiv, Ukraine
A. V. Gorokhovatskiy
Simon Kuznets Kharkiv National University of Economics, 9-A Nauka Ave., Kharkiv 61166, Ukraine
A. Ye. Berestovsky
Kharkiv National University of Radio Engineering and Electronics, 14, Lenin Ave, Kharkiv, 61166, Ukraine

SINOPSIS

The issues of enhancing efficiency of the structural image recognition methods in the computer vision systems are discussed. For the purpose of compression of the space of signs it is suggested to perform self-learning with application of Kohonen network. As the result, it is developed a more efficient in terms of processing fast-action method of recognition based on cluster vector description of the standards. The computer simulation results are provided for estimation of the quality of recognition for a variety of processing options in the application image database.

PALABRAS CLAVE: computer vision, structural image recognition methods, characteristic features, structural description, self-organization, the Kohonen network, clusterization, cluster representation, vector description, quality of recognition

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