Difference between revisions of "LRDE Document Binarization Dataset (LRDE DBD)"
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EPITA Research and Development Laboratory (LRDE) | EPITA Research and Development Laboratory (LRDE) | ||
14-16 rue Voltaire F-94276 Le Kremlin-Bicetre France | 14-16 rue Voltaire F-94276 Le Kremlin-Bicetre France | ||
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| + | =Copyright= | ||
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| + | LRDE is the copyright holder of all the images included in the dataset except for the original documents subset which are copyrighted from [http://www.nouvelobs.com/ Le Nouvel Observateur]. This work is based on the French magazine Le Nouvel Observateur, issue 2402, November 18th-24th, 2010. | ||
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| + | You are allowed to reuse these documents for research purpose for evaluation and illustration. If so, please specify the following copyright: "Copyright (c) 2012. EPITA Research and Development Laboratory (LRDE) with permission from Le Nouvel Observateur". You are not allowed to redistribute this dataset. | ||
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| + | If you use this dataset, please also cite the most appropriate paper from this list: | ||
| + | * [http://www.lrde.epita.fr/cgi-bin/twiki/view/Publications/201302-IJDAR Efficient Multiscale Sauvola's Binarization. In International Journal of Document Analysis and Recognition (IJDAR), 2013] | ||
| + | * [http://www.lrde.epita.fr/cgi-bin/twiki/view/Publications/201109-ICDAR The SCRIBO Module of the Olena Platform: a Free Software Framework for Document Image Analysis. In the proceedings of the 11th International Conference on Document Analysis and Recognition (ICDAR), 2011.] | ||
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| + | This data set is provided "as is" and without any express or implied warranties, including, without limitation, the implied warranties of merchantability and fitness for a particular purpose. | ||
=Current Version= | =Current Version= | ||
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=Description= | =Description= | ||
| − | This dataset is composed of documents images extracted from the same French magazine : Le Nouvel Observateur, issue 2402, November 18th-24th, 2010. | + | The dataset is also available at [http://www.lrde.epita.fr/cgi-bin/twiki/view/Olena/DatasetDBD http://www.lrde.epita.fr/cgi-bin/twiki/view/Olena/DatasetDBD] |
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| + | This dataset is composed of documents images extracted from the same French magazine: Le Nouvel Observateur, issue 2402, November 18th-24th, 2010. | ||
The provided dataset is composed of 375 Full-Document Images (A4 format, 300-dpi resolution) | The provided dataset is composed of 375 Full-Document Images (A4 format, 300-dpi resolution) | ||
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* 125 "scanned documents" based on the "clean documents". They have been printed, scanned and registered to match the "clean documents". | * 125 "scanned documents" based on the "clean documents". They have been printed, scanned and registered to match the "clean documents". | ||
| − | Purpose of the three document qualities : | + | Purpose of the three document qualities: |
* Original : evaluate the binarization quality on perfect documents mixing text and images. | * Original : evaluate the binarization quality on perfect documents mixing text and images. | ||
* Clean : evaluate the binarization quality on perfect document with text only. | * Clean : evaluate the binarization quality on perfect document with text only. | ||
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=Related Tasks= | =Related Tasks= | ||
* [[Document Binarization Evaluation for LRDE DBD]] | * [[Document Binarization Evaluation for LRDE DBD]] | ||
| + | * [[OCR Evaluation for LRDE DBD]] | ||
=Software= | =Software= | ||
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=Submitted Files= | =Submitted Files= | ||
==Version 1.0== | ==Version 1.0== | ||
| + | Please refer to [http://www.lrde.epita.fr/cgi-bin/twiki/view/Olena/DatasetDBD http://www.lrde.epita.fr/cgi-bin/twiki/view/Olena/DatasetDBD] for downloading the files from the origninal datasets site. | ||
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| + | * [http://www.iapr-tc11.org/dataset/LRDE/nouvel_obs_2402_orig-1.0.zip Original images] (213 Mb) | ||
| + | * [http://www.iapr-tc11.org/dataset/LRDE/nouvel_obs_2402_clean-1.0.zip Clean Documents images] (67 Mb) | ||
| + | * [http://www.iapr-tc11.org/dataset/LRDE/nouvel_obs_2402_scanned-1.0.zip Scanned Documents] (583 Mb) | ||
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This page is editable only by [[IAPR-TC11:Reading_Systems#TC11_Officers|TC11 Officers ]]. | This page is editable only by [[IAPR-TC11:Reading_Systems#TC11_Officers|TC11 Officers ]]. | ||
Latest revision as of 16:22, 3 July 2013
Datasets -> Datasets List -> Current Page
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Contents
Contact Author
Thierry Géraud – thierry.geraud@lrde.epita.fr EPITA Research and Development Laboratory (LRDE) 14-16 rue Voltaire F-94276 Le Kremlin-Bicetre France
Copyright
LRDE is the copyright holder of all the images included in the dataset except for the original documents subset which are copyrighted from Le Nouvel Observateur. This work is based on the French magazine Le Nouvel Observateur, issue 2402, November 18th-24th, 2010.
You are allowed to reuse these documents for research purpose for evaluation and illustration. If so, please specify the following copyright: "Copyright (c) 2012. EPITA Research and Development Laboratory (LRDE) with permission from Le Nouvel Observateur". You are not allowed to redistribute this dataset.
If you use this dataset, please also cite the most appropriate paper from this list:
- Efficient Multiscale Sauvola's Binarization. In International Journal of Document Analysis and Recognition (IJDAR), 2013
- The SCRIBO Module of the Olena Platform: a Free Software Framework for Document Image Analysis. In the proceedings of the 11th International Conference on Document Analysis and Recognition (ICDAR), 2011.
This data set is provided "as is" and without any express or implied warranties, including, without limitation, the implied warranties of merchantability and fitness for a particular purpose.
Current Version
1.0
Keywords
Document binarization, Magazine, Scanned
Description
The dataset is also available at http://www.lrde.epita.fr/cgi-bin/twiki/view/Olena/DatasetDBD
This dataset is composed of documents images extracted from the same French magazine: Le Nouvel Observateur, issue 2402, November 18th-24th, 2010.
The provided dataset is composed of 375 Full-Document Images (A4 format, 300-dpi resolution)
- 125 numerical "original documents" extracted from a PDF, with full OCR groundtruth.
- 125 numerical "clean documents" created from the "original documents" where images have been removed.
- 125 "scanned documents" based on the "clean documents". They have been printed, scanned and registered to match the "clean documents".
Purpose of the three document qualities:
- Original : evaluate the binarization quality on perfect documents mixing text and images.
- Clean : evaluate the binarization quality on perfect document with text only.
- Scanned : evaluate the binarization quality on slightly degraded documents with text only.
Ground Truth Data
- Ground Truth for LRDE DBD text line localization
- Ground Truth for LRDE DBD binarization
- Ground Truth for LRDE DBD OCR
Related Tasks
Software
- A setup script is provided to download and configure the benchmarking environment. This is the recommanded way to run this benchmark. Note that this script also includes features to update the dataset if a new version is released.
- A Python script is provided to launch the benchmark and compute scores.
- C++ programs (and sources) are provided for performing evaluations and reading ground-truth data.
- 6 binarization algorithms (and their respective C++ sources) are provided and compiled to run this benchmark on their results.
Minimum requirements: 5GB of free space, Linux (Ubuntu, Debian, …)
Dependencies: Python 2.7, tesseract-ocr, tesseract-ocr-fra, git, libgraphicsmagick++1-dev, graphicsmagick-imagemagick-compat, graphicsmagick-libmagick-dev-compat, build-essential. libtool. automake, autoconf. g++-4.6, libqt4-dev (installed automatically with the setup script on Ubuntu and Debian).
References
- G. Lazzara, T. Géraud. Efficient Multiscale Sauvola's Binarization. In International Journal of Document Analysis and Recognition 2013 [[1]]
Submitted Files
Version 1.0
Please refer to http://www.lrde.epita.fr/cgi-bin/twiki/view/Olena/DatasetDBD for downloading the files from the origninal datasets site.
- Original images (213 Mb)
- Clean Documents images (67 Mb)
- Scanned Documents (583 Mb)
This page is editable only by TC11 Officers .