Modelling the Flow of Character Recognition Results in Video Stream

V. V. Arlazarov; O. A. Slavin; A. V. Uskov; I. M. Janiszewski

doi:10.14529/mmp180202

Authors

V. V. Arlazarov Federal Research Center "Informatics and Management" of RAS
O. A. Slavin Federal Research Center "Informatics and Management" of RAS
A. V. Uskov Federal Research Center "Informatics and Management" of RAS
I. M. Janiszewski Federal Research Center "Informatics and Management" of RAS

DOI:

https://doi.org/10.14529/mmp180202

Keywords:

stochastic model, video stream, the character recognition, Dirichlet distribution, Akaike criterion, goodness-of-t Anderson-Darling tests.

Abstract

The paper considers problems of developing stochastic models consistent with results of character image recognition in video stream. A set of assumptions that dene the models structure and properties is stated. A class of distributions, namely the Dirichlet distribution and its generalizations, that set a description of the model components is pointed out; and methods for statistical estimation of the distribution parameters are given. To rank the models, the Akaike information criterion is used. The proposed theoretical distributions are veried vs sample data.

Author Biographies

V. V. Arlazarov, Federal Research Center "Informatics and Management" of RAS

Candidate of Engineering Sciences

O. A. Slavin, Federal Research Center "Informatics and Management" of RAS

Doctor of Engineering Sciences

A. V. Uskov, Federal Research Center "Informatics and Management" of RAS

Candidate of Physico-Mathematical Sciences

I. M. Janiszewski, Federal Research Center "Informatics and Management" of RAS

Candidate of Physico-Mathematical Sciences

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