| HA, Hien Thi, Aleš HORÁK, Marek MEDVEĎ and Zuzana NEVĚŘILOVÁ. Recognition of OCR Invoice Metadata Block Types. In P. Sojka, A. Horák, I. Kopeček, K. Pala. Text, Speech, and Dialogue, 21st International Conference, TSD 2018. Switzerland: Springer International Publishing, 2018, p. 304-312. ISBN 978-3-030-00793-5. Available from: https://dx.doi.org/10.1007/978-3-030-00794-2_33. |
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@inproceedings{1421338,
author = {Ha, Hien Thi and Horák, Aleš and Medveď, Marek and Nevěřilová, Zuzana},
address = {Switzerland},
booktitle = {Text, Speech, and Dialogue, 21st International Conference, TSD 2018},
doi = {http://dx.doi.org/10.1007/978-3-030-00794-2_33},
editor = {P. Sojka, A. Horák, I. Kopeček, K. Pala},
keywords = {OCR;scanned documents;document metadata;invoice metadata extraction},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Switzerland},
isbn = {978-3-030-00793-5},
pages = {304-312},
publisher = {Springer International Publishing},
title = {Recognition of OCR Invoice Metadata Block Types},
year = {2018}
}
TY - JOUR
ID - 1421338
AU - Ha, Hien Thi - Horák, Aleš - Medveď, Marek - Nevěřilová, Zuzana
PY - 2018
TI - Recognition of OCR Invoice Metadata Block Types
PB - Springer International Publishing
CY - Switzerland
SN - 9783030007935
KW - OCR;scanned documents;document metadata;invoice metadata extraction
N2 - Automatically cataloging of thousands of paper-based structured documents is a crucial fund-saving task for future document management systems. Current optical character recognition (OCR) systems process the tabular data with a sufficient level of character-level accuracy; however, the overall structure of the document metadata is still an open practical task. In this paper, we introduce the OCRMiner system designed to extract the indexing metadata of structured documents obtained from an image scanning process and OCR. We present the details of the system modular architecture and evaluate the detection of text block types that appear within invoice documents. The system is based on text analysis in combination of layout features, and is developed and tested in cooperation with a renowned copy machine producer. The system uses an open source OCR and reaches the overall accuracy of 80.1%.
ER -
HA, Hien Thi, Aleš HORÁK, Marek MEDVEĎ and Zuzana NEVĚŘILOVÁ. Recognition of OCR Invoice Metadata Block Types. In P. Sojka, A. Horák, I. Kopeček, K. Pala. \textit{Text, Speech, and Dialogue, 21st International Conference, TSD 2018}. Switzerland: Springer International Publishing, 2018, p.~304-312. ISBN~978-3-030-00793-5. Available from: https://dx.doi.org/10.1007/978-3-030-00794-2\_{}33.
|
