Generation of Synthetic Images of Full-Text Documents

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43952605" target="_blank" >RIV/49777513:23520/18:43952605 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-99579-3_8" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-99579-3_8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-99579-3_8" target="_blank" >10.1007/978-3-319-99579-3_8</a>

Result language
angličtina
Original language name
Generation of Synthetic Images of Full-Text Documents
Original language description
In this paper, we present an algorithm for generating images of full-text documents. Such images can be used to train and evaluate models of optical character recognition. The algorithm is modular, individual parts can be changed and tweaked to generate desired images. We describe a method for obtaining background images of paper from already digitalized documents.We use a Variational Autoencoder to train a generative model of these backgrounds enabling the generation of similar background images as the training ones on the fly. The module for printing the text uses large text corpora, font, and suitable positional and brightness noise to obtain believable results. We use Tesseract OCR to compare the real world and generated images and observe that the recognition rate is very similar indicating the proper appearance of the synthetic images. Furthermore, the mistakes made by the OCR system in both cases are alike. Finally, the system generates detailed, structured annotation of the synthesized image.
Czech name
—
Czech description
—

Project
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Speech and Computer 20th International Conference, SPECOM 2018 Leipzig, Germany, September 18–22, 2018, Proceedings
ISBN
978-3-319-99578-6
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
8
Pages from-to
68-75
Publisher name
Springer Nature Switzerland AG
Place of publication
Cham
Event location
Leipzig, Germany
Event date
Sep 18, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

Similar results(10)