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

  • Medical and Biological Measurements
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Measurement Techniques Aims and scope

Abstract

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.

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Authors and Affiliations

  1. Penza State University, Penza, Russia

    N. G. Fedotov, A. S. Kol’chugin & O. A. Smol’kin

  2. All-Russia Financial-Economic Correspondence Institute (Penza Branch), Penza, Russia

    A. V. Moiseev & S. V. Romanov

Authors
  1. N. G. Fedotov
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  2. A. S. Kol’chugin
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  3. O. A. Smol’kin
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  4. A. V. Moiseev
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  5. S. V. Romanov
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Corresponding author

Correspondence to N. G. Fedotov.

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Translated from Izmeritel’naya Tekhnika, No. 2, pp. 56–61, February, 2008.

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Fedotov, N.G., Kol’chugin, A.S., Smol’kin, O.A. et al. The formation of features for recognizing complex images based on stochastic geometry. Meas Tech 51, 199–207 (2008). https://doi.org/10.1007/s11018-008-9002-8

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  • DOI: https://doi.org/10.1007/s11018-008-9002-8

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