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Proceedings Paper

Experimental modeling the flow of character recognition results in video stream for document recognition
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Paper Abstract

This paper considers problems regarding the development of stochastic models consistent with the results of character image recognition in video stream. Assumptions about their structure and properties are formulated for the constructed models. The description of the model components defines the Dirichlet distribution and its generalizations. The parameters of these distributions are determined using statistical estimation methods. The Akaike information criterion is used to rank models. The verification of the agreement of the proposed theoretical distributions to the sample data is carried out.

Paper Details

Date Published: 15 March 2019
PDF: 6 pages
Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110411L (15 March 2019); doi: 10.1117/12.2522970
Show Author Affiliations
Elena Andreeva, Smart Engines Ltd. (Russian Federation)
Moscow Institute of Physics and Technology (Russian Federation)
Vladimir V. Arlazarov, Institute for Systems Analysis (Russian Federation)
Smart Engines Ltd. (Russian Federation)
Oleg Slavin, Institute for Systems Analysis (Russian Federation)
Smart Engines Ltd. (Russian Federation)
Igor Janiszewski, Institute for Systems Analysis (Russian Federation)


Published in SPIE Proceedings Vol. 11041:
Eleventh International Conference on Machine Vision (ICMV 2018)
Antanas Verikas; Dmitry P. Nikolaev; Petia Radeva; Jianhong Zhou, Editor(s)

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