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Proceedings Paper

Recognition algorithms of multilevel images of multicharacter identification objects based on nonlinear equivalent metrics and analysis of experimental data
Author(s): Vladimir G. Krasilenko; Alexander I. Nikolsky; Yuriy A. Bozniak
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Paper Abstract

The given paper suggest recognition algorithms of multilevel images of multicharacter identification objects. These algorithms are based on application of linear (nonlinear) equivalent (nonequivalent) space-dependent similarity means of normalized matrix data as criterial (discriminant) functions. The results of modeling and experimental results have shown that such nonlinear-equivalent algorithms process higher discriminant properties and operating characteristics, especially in case of considerable (up to 50 %) noise level content of images.

Paper Details

Date Published: 6 March 2002
PDF: 10 pages
Proc. SPIE 4731, Sensor Fusion: Architectures, Algorithms, and Applications VI, (6 March 2002); doi: 10.1117/12.458380
Show Author Affiliations
Vladimir G. Krasilenko, Enterprise Technicom (Ukraine)
Alexander I. Nikolsky, Vinnitsa State Technical Univ. (Ukraine)
Yuriy A. Bozniak, Vinnitsa State Technical Univ. (Ukraine)


Published in SPIE Proceedings Vol. 4731:
Sensor Fusion: Architectures, Algorithms, and Applications VI
Belur V. Dasarathy, Editor(s)

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