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ICDAR2019 Competition on Recognition of Early Indian Printed Documents – REID2019 Public Deposited

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Resource type
  • Conference paper (unpublished)
Creator
  • Clausner, Christian
  • Antonacopoulos, Apostolos
  • Derrick, Tom
  • Pletschacher, Stefan
Abstract
  • This paper presents an objective comparative evaluation of page analysis and recognition methods for historical documents with text mainly in Bengali language and script. It describes the competition rules, dataset, and evaluation methodology. Results are presented for five methods - three submit-ted, one re-run, and one open source state-of-the-art system. The focus is on optical character recognition (OCR) performance. Different evaluation metrics were used to gain an in-sight into the algorithms, including new character accuracy metrics to better reflect the difficult circumstances presented by the documents. The results indicate that deep learning approaches are promising, but there are still significant challenges for historic material of this nature.
Date published
  • 2019-9
Institution
  • British Library
Organisational unit
  • Digital Scholarship
Event title
  • 2019 International Conference on Document Analysis and Recognition (ICDAR)
Event location
  • Sydney, Australia
Book title
  • Proceedings of the 15th IAPR International Conference on Document Analysis and Recognition ICDAR 2019
Publisher
  • IEEE
ISBN
  • 9781728130149
ISSN
  • 2379-2140
eISSN
  • 1520-5363
Official URL Rights holder
  • Institute of Electrical and Electronics Engineers, Inc
Related identifier
  • relation: Is Metadata For
Additional Information
  • © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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