Recognition of OCR Invoice Metadata Block Types

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F18%3A00103049" target="_blank" >RIV/00216224:14330/18:00103049 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-030-00794-2_33" target="_blank" >http://dx.doi.org/10.1007/978-3-030-00794-2_33</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-00794-2_33" target="_blank" >10.1007/978-3-030-00794-2_33</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Recognition of OCR Invoice Metadata Block Types

Popis výsledku v původním jazyce

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%.

Název v anglickém jazyce

Recognition of OCR Invoice Metadata Block Types

Popis výsledku anglicky

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%.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Text, Speech, and Dialogue, 21st International Conference, TSD 2018

ISBN

9783030007935

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

9

Strana od-do

304-312

Název nakladatele

Springer International Publishing

Místo vydání

Switzerland

Místo konání akce

Brno, Czech Republic

Datum konání akce

1. 1. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000611532300033