Mr Christian Clausner C.Clausner@salford.ac.uk
Senior Research Fellow
ICFHR 2018 Competition on recognition of historical Arabic scientific manuscripts - RASM2018
Clausner, C; Antonacopoulos, A; McGregor, N; Wilson-Nunn, D
Authors
Prof Apostolos Antonacopoulos A.Antonacopoulos@salford.ac.uk
Professor
N McGregor
D Wilson-Nunn
Abstract
This paper presents an objective comparative evaluation of page analysis and recognition methods for historical scientific manuscripts with text in Arabic language and script. It describes the competition (modus operandi, dataset and evaluation methodology) held in the context of ICFHR2018, presenting the results of the evaluation of six methods – three submitted and three baseline systems. The challenges for the participants included page segmentation, text line detection, and optical character recognition (OCR). Different evaluation metrics were used to gain an insight into the algorithms, including new character accuracy metrics to better reflect the difficult circumstances presented by the documents. The results indicate that, despite the challenging nature of the material, useful digitisation outputs can be produced.
Citation
Clausner, C., Antonacopoulos, A., McGregor, N., & Wilson-Nunn, D. (2018). ICFHR 2018 Competition on recognition of historical Arabic scientific manuscripts - RASM2018. . https://doi.org/10.1109/ICFHR-2018.2018.00088
Conference Name | 17th International Conference on Frontiers in Handwriting Recognition (ICFHR2018) |
---|---|
Conference Location | Niagara Falls, USA |
Start Date | Aug 5, 2018 |
End Date | Aug 8, 2018 |
Acceptance Date | Jun 29, 2018 |
Online Publication Date | Dec 20, 2018 |
Publication Date | Dec 20, 2018 |
Deposit Date | Jan 29, 2019 |
Publicly Available Date | Jan 29, 2019 |
DOI | https://doi.org/10.1109/ICFHR-2018.2018.00088 |
Publisher URL | https://doi.org/10.1109/ICFHR-2018.2018.00088 |
Related Public URLs | http://icfhr2018.org/index.html |
Files
ICFHR2018_Clausner_RASM.pdf
(1.1 Mb)
PDF
You might also like
A survey of OCR evaluation tools and metrics
(2021)
Conference Proceeding
VISE : an interface for Visual Search and Exploration of museum collections
(2019)
Journal Article
Efficient and effective OCR engine training
(2019)
Journal Article
Downloadable Citations
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search