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

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

Bibliographic Details
Parent link:Control and Communications (SIBCON-2017): proceedings of the XIII International Siberian Conference, June 29–30, 2017, Astana, Kazakhstan. [17082656].— , 2017
Corporate Author: Национальный исследовательский Томский политехнический университет (ТПУ) Институт кибернетики (ИК) Кафедра информационных систем и технологий (ИСТ)
Other Authors: Osina P. M. Polina Maksimovna, Bolotova Yu. A. Yuliya Aleksandrovna, Spitsyn V. G. Vladimir Grigorievich
Summary:Title screen
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.
Режим доступа: по договору с организацией-держателем ресурса
Published: 2017
Subjects:
электронный ресурс
труды учёных ТПУ
text detection
discrete cosine transform
artificial neural network
convolution neural networks
machine learning
optical character recognition
тексты
преобразование
нейронные сети
машинное обучение
оптическое распознавание
символы
Online Access:https://doi.org/10.1109/SIBCON.2017.7998591
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=656804

Internet

https://doi.org/10.1109/SIBCON.2017.7998591

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