TYPED DIGITS RECOGNITION USING SEQUENTIAL PROBABILITY RATIO TEST

Authors

  • Volodymyr Kharchenko National Aviation University
  • Iurii Chyrka National Aviation University

DOI:

https://doi.org/10.18372/2306-1472.74.12286

Keywords:

Bayesian classifier, digits recognition, neural network, sequential test

Abstract

Purpose: the represented research results are aimed to better understanding of computer vision methods and their capabilities. Both the statistical classifier and an artificial neural network allows processing of typical objects with simple descriptors. Methods: considered methods are grounded at probabilistic theory, optimization theory, kernel density estimation and computer-based simulation as a verification tool. Results: the considered artificial neural network architecture for digits recognition has advantage in comparison with statistical method due to its better classification ability. Presented results of experimental verification prove that advantage in both single observation and sequential observation scenarios. Discussion: the approach can be implemented in a variety of computer vision systems that observe typed text in difficult noisy conditions.

Author Biographies

Volodymyr Kharchenko, National Aviation University

Doctor of Engineering. Professor.

Vice-Rector on Scientific Work, National Aviation University, Kyiv, Ukraine.

Editor-in-Chief of the scientific journal Proceedings of the National Aviation University.

Winner of the State Prize of Ukraine in Science and Technology, Honored Worker of Science and Technology of Ukraine.

Education: Kyiv Institute of Civil Aviation Engineers, Kyiv, Ukraine.

Research area: management of complex socio-technical systems, air navigation systems and automatic decision-making systems aimed at avoidance conflict situations, space information technology design, air navigation services in Ukraine provided by CNS/ATM systems.

Iurii Chyrka, National Aviation University

Candidate of Engineering Sciences. Senior Researcher.

National Aviation University.

Education: National Aviation University, Kyiv, Ukraine (2011).

Research area: control systems, radar signals processing, acoustic holography, and applied statistics.

References

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Dong Xiao Ni Seidenberg, “Application of Neural Networks to Character Recognition”, CSIS, Pace University, School of CSIS, Pace University, White Plains, NY, 2007

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Wasserman L. (2006). All of Nonparametric Statistics. Springer Texts in Statistics. New York, NY, Springer, 268 p.

Kharchenko V.P., Kukush A.G., Kuzmenko N.S., and Ostroumov I.V. (2017) Probabilistic Approach to Object Detection and Recognition for Videostream Processing. Proceedings of the NAU, No. 2(71), pp. 8–14. doi: 10.18372/2306-1472.71.11741

Kharchenko V., Pawęska M., Bugayko D., Antonova A., Grigorak M. (2017) Theoretical Approaches for Safety Levels Measurements–Sequential Probability Ratio Test (SPRT). Logistics and Transport, no. 2(34), p.p. 25-32.

Published

01-02-2018

How to Cite

Kharchenko, V., & Chyrka, I. (2018). TYPED DIGITS RECOGNITION USING SEQUENTIAL PROBABILITY RATIO TEST. Proceedings of National Aviation University, 74(1), 38–44. https://doi.org/10.18372/2306-1472.74.12286

Issue

Section

AEROSPACE SYSTEMS FOR MONITORING AND CONTROL

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