The formation of features for recognizing complex images based on stochastic geometry

The theory of obtaining the features of pattern recognition based on stochastic geometry and having a three-functional structure (triplet features) is presented. The effectiveness of the proposed method of forming features for recognizing complex-structured and semantically saturated images is prove...

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Veröffentlicht in:	Measurement techniques 2008-02, Vol.51 (2), p.199-207
Hauptverfasser:	Fedotov, N. G., Kol’chugin, A. S., Smol’kin, O. A., Moiseev, A. V., Romanov, S. V.
Format:	Artikel
Sprache:	eng
Schlagworte:	Analytical Chemistry Characterization and Evaluation of Materials Diagnostics Geometry Investigations Measurement Science and Instrumentation Measurement techniques Medical and Biological Measurements Pattern recognition Physical Chemistry Physics Physics and Astronomy Stochastic models Studies
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	The theory of obtaining the features of pattern recognition based on stochastic geometry and having a three-functional structure (triplet features) is presented. The effectiveness of the proposed method of forming features for recognizing complex-structured and semantically saturated images is proved. A practical example of the formation of features for images from the area of medical diagnostics is considered.
ISSN:	0543-1972 1573-8906
DOI:	10.1007/s11018-008-9002-8