Russian Psychological Issues PsyJournals.ru
OPEN ACCESS JOURNALS
JournalsTopicsAuthorsEditor's Choice Manuscript SubmissionAbout PsyJournals.ruContact Us
Psychological Science and Education - №4 / 2022 | Перейти к описанию
Scopus
Web of Science СС

  Previous issue (2022. Vol. 27, no. 3)

Included in Scopus

Journal Quartiles 2021

CiteScore : Q3
SNIP: Q2
SJR: Q3

Details on scimagojr.com/

CrossRef

Psychological Science and Education

Publisher: Moscow State University of Psychology and Education

ISSN (printed version): 1814-2052

ISSN (online): 2311-7273

DOI: https://doi.org/10.17759/pse

License: CC BY-NC 4.0

Published since 1996

Published 6 times a year

Free of fees
Open Access Journal

 

Character Recognition Based on the Markov Chains 1192

|

Yuryev G.A.
PhD in Physics and Matematics, Associate Professor, Head of Scientifi c Laboratory, Moscow State University of Psychology and Education, Moscow, Russia
ORCID: https://orcid.org/0000-0002-2960-6562
e-mail: g.a.yuryev@gmail.com

Abstract
A fundamentally new algorithm for character recognition is described, which is based on the abilities of the Markov chains [1; 5] – the Markov models with discrete states and discrete time. The applied apparatus is widely used in solving the problems of recognition, but it is noted that traditionally it has been used somewhat differently. The advantage of this method is the high speed of the tuning (teaching), the ability to specify the arbitrary and required reliability of the result and to modify it in the work process of the program system. The algorithm is successfully implemented in the El-Reader [2; 3; 4] – a system of recognition and vocalization of the flat bed texts. The main advantage of it is its resistance to change in the font styles. The prerequisites for the development, theoretical justification and description of the algorithm used in the software implementation are provided in the article. The accurate statistical evaluation of the reliability of recognition for the given parameters is presented. It is emphasized that the algorithm has a number of advantages over traditional approaches, in case of working with the distorted images.

Keywords: Markov chains, recognition, wavelet transformation, image analysis

Column: Interdisciplinary Researches

For Reference

References
  1. Kuravskij L. S., Yuryev G. A. Raspoznavanie i ozvuchivanie tekstov dlja oblegchenija obuchenija ljudej s narushenijami zrenija // Psihologicheskaja nauka i obrazovanie. 2009. № 5.
  2. Kuravskij L. S., Yuryev G. A. Tehnologija raspoznavanija i ozvuchivanija tekstov dlja ljudej s narushenijami zrenija // Nejrokomp'jutery: razrabotka, primenenie. 2009. № 9.
  3. Ovcharov L. A. Prikladnye zadachi teorii massovogo obsluzhivanija. M., 1969.
  4. Svid. № 2009613028 ob ofic. reg. progr. dlja JeVM. El-Reader. Programmnoe obespechenie raspoznavanija i ozvuchivanija tekstov dlja ljudej s narushenijami zrenija / G. A. Yuryev, L. S. Kuravskij. M.: RosPatent, 2009.
  5. Kuravsky L. S., Baranov S. N. Synthesis of Markov networks for forecasting fatigue failures. In: Proc. Condition Monitoring 2003, Oxford, United Kingdom, July 2003.
 
About PsyJournals.ru

© 2007–2022 Portal of Russian Psychological Publications. All rights reserved

PsyJournals.ru in Russian

Publisher: Moscow State University of Psychology and Education

Catalogue of academic journals in psychology & education MSUPE

Creative Commons License Open Access Repository     Webometrics Ranking of Repositories

RSS Psyjournals at Youtube ??????.???????