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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

Volumes:
Volumen 78, 2019 Volumen 77, 2018 Volumen 76, 2017 Volumen 75, 2016 Volumen 74, 2015 Volumen 73, 2014 Volumen 72, 2013 Volumen 71, 2012 Volumen 70, 2011 Volumen 69, 2010 Volumen 68, 2009 Volumen 67, 2008 Volumen 66, 2007 Volumen 65, 2006 Volumen 64, 2005 Volumen 63, 2005 Volumen 62, 2004 Volumen 61, 2004 Volumen 60, 2003 Volumen 59, 2003 Volumen 58, 2002 Volumen 57, 2002 Volumen 56, 2001 Volumen 55, 2001 Volumen 54, 2000 Volumen 53, 1999 Volumen 52, 1998 Volumen 51, 1997

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.


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