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Recognition of OCR Invoice Metadata Block Types

  • Hien T. Ha
  • Marek Medved’
  • Zuzana Nevěřilová
  • Aleš Horák
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11107)

Abstract

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%.

Keywords

OCR Scanned documents Document metadata Invoice metadata extraction 

Notes

Acknowledgments

This work has been partly supported by Konica Minolta Business Solution Czech within the OCR Miner project and by the Masaryk University project MUNI/33/55939/2017.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Hien T. Ha
    • 1
  • Marek Medved’
    • 1
  • Zuzana Nevěřilová
    • 1
  • Aleš Horák
    • 1
  1. 1.Natural Language Processing Centre, Faculty of InformaticsMasaryk UniversityBrnoCzech Republic

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