Datasets List - Revision history

Jchazalon: /* Mixed Content Documents */

2019-09-20T07:21:55Z

‎Mixed Content Documents

Dimos at 16:05, 22 January 2015

2015-01-22T16:05:06Z

Dimos: /* Software and Tools */

2014-07-23T14:01:53Z

‎Software and Tools

Dimos: /* Mixed Content Documents */

2014-02-06T10:20:41Z

‎Mixed Content Documents

Liwicki: /* Software and Tools */

2013-08-24T21:01:45Z

‎Software and Tools

Liwicki: /* Machine-printed Documents */

2013-08-24T20:52:21Z

‎Machine-printed Documents

Liwicki: /* Off-line */

2013-08-24T11:50:13Z

‎Off-line

Liwicki: /* On-line and Off-line */

2013-05-30T18:20:36Z

‎On-line and Off-line

Liwicki: /* Machine-printed Documents */

2013-05-30T16:43:46Z

‎Machine-printed Documents

Dimos: /* Machine-printed Documents */

2013-05-27T10:18:48Z

‎Machine-printed Documents

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 = Mixed Content Documents =
-* [http://www.umiacs.umd.edu/~zhugy/tobacco800.html Tobacco800 Document Image Database] - composed of 1290 document images collected and scanned using a wide variety of equipment over time.
+* [http://dataset.iapr-tc11.org/datasets/Tobacco800_1 Tobacco800 Document Image Database] - composed of 1290 document images collected and scanned using a wide variety of equipment over time.
 = Handwritten Documents =

← Older revision		Revision as of 16:05, 22 January 2015
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		+	NOTICE: TC11 datasets will be soon moved to the new Web portal at http://tc11.cvc.uab.es This page will remain available but will not be updated from January 2015 onwards.
		+
	[[Datasets]] -> [[Datasets List]]		[[Datasets]] -> [[Datasets List]]

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 = Software and Tools =
 * [http://www.digitisation.eu/tools/ Tools from the IMPACT Centre of Competence] The tools offered by the Impact Centre of Competence are software components which have been developed by the different technical IMPACT partners during the IMPACT project (2008-2012). Generally, a "tool" is a piece of software which operates on image or text data modifying the data or extracting information from it. Every IMPACT tool has a specific functionality related to OCR, to the the pre- and post-processing stages. They include new approaches in areas such as image enhancement, segmentation, and document structuring, alongside existing and experimental OCR engines.
 * [http://lampsrv02.umiacs.umd.edu/projdb/project.php?id=53 GEDI: Groundtruthing Environment for Document Images] - A generic annotation tool for scanned text documents.

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 = Mixed Content Documents =
-* [http://www.umiacs.umd.edu/~zhugy/Tobacco800.html Tobacco800 Document Image Database] - composed of 1290 document images collected and scanned using a wide variety of equipment over time.
+* [http://www.umiacs.umd.edu/~zhugy/tobacco800.html Tobacco800 Document Image Database] - composed of 1290 document images collected and scanned using a wide variety of equipment over time.
 = Handwritten Documents =

@@ Line 102: / Line 102: @@
 = Software and Tools =
 * [http://lampsrv02.umiacs.umd.edu/projdb/project.php?id=53 GEDI: Groundtruthing Environment for Document Images] - A generic annotation tool for scanned text documents.
 * [http://www2.parc.com/isl/groups/pda/pixlabeler/index.html PixLabeler] - a research tool for labeling elements in a document image at a pixel level.

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 * [[Table Ground Truth for the UW3 and UNLV datasets]]
 * [[The DocLab Dataset for Evaluating Table Interpretation Methods]]
 * [http://dataset.primaresearch.org/ PRImA Layout Analysis Dataset]
 * [http://www.dfki.uni-kl.de/~shafait/downloads.html DFKI Dewarping Contest Dataset (CBDAR 2007)] The dataset, that was used in the CBDAR 2007 Dewarping Contest, contains 102 camera captured documents with their corresponding ASCII text ground-truth. Additionally, text-line level ground-truth was also prepared to benchmark curled text-line segmentation algorithms. Part of the dataset (76 out of 102 pages) were also scanned with a flat-bed scanner to create a ground-truth image for image based evaluation of page dewarping algorithms.

← Older revision		Revision as of 11:50, 24 August 2013
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	* [http://www.cedar.buffalo.edu/Databases/CDROM1/ CEDAR Off-line Handwriting CDROM1]		* [http://www.cedar.buffalo.edu/Databases/CDROM1/ CEDAR Off-line Handwriting CDROM1]
		+
		+	* [[CVL-Database]] - An Off-line Database for Writer Retrieval, Writer Identification and Word Spotting

	* [http://www.iam.unibe.ch/fki/databases/iam-handwriting-database IAM Database] - A full English sentence database for off-line handwriting recognition.		* [http://www.iam.unibe.ch/fki/databases/iam-handwriting-database IAM Database] - A full English sentence database for off-line handwriting recognition.

← Older revision		Revision as of 18:20, 30 May 2013
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	* [http://www.nlpr.ia.ac.cn/databases/handwriting/Home.html CASIA Online and Offline Chinese Handwriting Databases] - The Chinese handwriting datasets were produced by 1,020 writers using Anoto pen on papers, such that both online and offline data were obtained. Both the online and the offline dataset consists of three subsets for isolated characters (DB1.0–1.2, about 3.9 million samples of 7,356 classes) and three for handwritten texts (DB2.0–2.2, about 5,090 pages and 1.35 million characters). The datasets are free for academic research for handwritten document segmentation and retrieval, character and text line recognition, writer adaptation and identification.		* [http://www.nlpr.ia.ac.cn/databases/handwriting/Home.html CASIA Online and Offline Chinese Handwriting Databases] - The Chinese handwriting datasets were produced by 1,020 writers using Anoto pen on papers, such that both online and offline data were obtained. Both the online and the offline dataset consists of three subsets for isolated characters (DB1.0–1.2, about 3.9 million samples of 7,356 classes) and three for handwritten texts (DB2.0–2.2, about 5,090 pages and 1.35 million characters). The datasets are free for academic research for handwritten document segmentation and retrieval, character and text line recognition, writer adaptation and identification.
		+
		+	* [[Persian Heritage Image Binarization Dataset (PHIBD 2012)]] This dataset contains 15 historical and old manuscript images collected from the historical records at the Documents and old manuscripts treasury of Mirza Mohammad Kazemaini (affiliated with Hazrate Emamzadeh Jafar), Yazd, Iran. The images suffer from various types of degradation including bleed-through, faded ink, and blur. The dataset is the first in a series to provide document images and their ground truth as a contribution to Document image analysis and recognition (DAIR) community. It is planned to provide more data and ground-truth information in the fture.

	== On-line ==		== On-line ==

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 * [http://www.dfki.uni-kl.de/~shafait/downloads.html DFKI Dewarping Contest Dataset (CBDAR 2007)] The dataset, that was used in the CBDAR 2007 Dewarping Contest, contains 102 camera captured documents with their corresponding ASCII text ground-truth. Additionally, text-line level ground-truth was also prepared to benchmark curled text-line segmentation algorithms. Part of the dataset (76 out of 102 pages) were also scanned with a flat-bed scanner to create a ground-truth image for image based evaluation of page dewarping algorithms.
 * [http://diuf.unifr.ch/diva/APTI/ APTI: Arabic Printed Text Image Database]
-* [LRDE Document Binarization Dataset (LRDE DBD)]
+* [[LRDE Document Binarization Dataset (LRDE DBD)]] 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).
 * [http://ciir.cs.umass.edu/downloads/ocr-evaluation/ RETAS OCR Evaluation Dataset] The RETAS dataset (used in the paper by Yalniz and Manmatha, ICDAR'11) is created to evaluate the optical character recognition (OCR) accuracy of real scanned books. The dataset contains real OCR outputs for 160 scanned books (100 English, 20 French, 20 German, 20 Spanish) downloaded from the Internet Archive website. The corresponding ground truth text for each scanned book is obtained from the Project Gutenberg database. The OCR output of each scanned book is aligned with its ground truth at the word and character level and the alignment output is provided along with estimated OCR accuracies. The dataset is provided for research purposes.