Text detection algorithm on real scenes images and videos on the base of discrete cosine transform and convolutional neural network

Polina M. Osina, Yuliya A. Bolotova, Vladimir G. Spitsyn

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work we present algorithms which are applied in such task as text recognition on images and video. Proposed algorithm is based on the combination of discrete cosine transform and convolutional neural networks. Description of the applying features of discrete cosine transform for text detection is provided. We list the main advantages and disadvantages of CNN and DCT combination. Also in this article we are going to consider methods of convolution neural networks for the task of text recognition.

Original languageEnglish
Title of host publication2017 International Siberian Conference on Control and Communications, SIBCON 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509010806
DOIs
Publication statusPublished - 31 Jul 2017
Event2017 International Siberian Conference on Control and Communications, SIBCON 2017 - Astana, Kazakhstan
Duration: 29 Jun 201730 Jun 2017

Conference

Conference2017 International Siberian Conference on Control and Communications, SIBCON 2017
CountryKazakhstan
CityAstana
Period29.6.1730.6.17

Keywords

  • artificial neural network
  • convolution neural networks
  • discrete cosine transform
  • machine learning
  • optical character recognition
  • Text detection

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Control and Optimization
  • Electrical and Electronic Engineering
  • Mechanical Engineering

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  • Cite this

    Osina, P. M., Bolotova, Y. A., & Spitsyn, V. G. (2017). Text detection algorithm on real scenes images and videos on the base of discrete cosine transform and convolutional neural network. In 2017 International Siberian Conference on Control and Communications, SIBCON 2017 - Proceedings [7998591] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIBCON.2017.7998591