aims to develop innova- tive, efficient and cost...
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Supported by: EU Cultural Heritage: http://www.transcriptorium.eu aims to develop innova- tive, efcient and cost-effective solu- tions for the indexing, search and full transcription of historical handwritten document images, using modern, holis- tic Handwritten Text Recognition tech- nology. ..................................................................................................................... will turn Handwritten Text Recog- nition (HTR) technology into a mature tech- nology by addressing the following objectives: 1 Enhancing HTR technology for efcient tran- scription Departing from state-of-the-art HTR approaches, will capitalize on interactive-predictive techniques for effective and user-friendly computer- assisted transcrition. 2 Bringing the HTR technology to users Expected users of the HTR technology belong mainly to two groups: a) individual researchers with expe- rience in handwritten documents transcription inter- ested in transcribing specic documents. b) volun- teers which collaborate in large transcription projects. 3 Integrating the HTR results in public web portals The HTR technology will become a support in the digitization of the handwritten materials. The out- comes of the tools will be attached to the published handwritten document images. This in- cludes not only full, correct transcriptions, but also partially correct transcription and other kinds of auto- matically produced metadata, useful for indexing and searching. Project coordinator: Joan Andreu S · anchez ([email protected]) Project no.: 600707 Start date: 1 January 2013 End date: 31 December 2015 ..................................................................................................................... Research groups and institutions: Pattern Recognition and Human Language Tech- nology Research Center (PRHLT) from Univer- sitat Politecnica de Val encia (Spain) Principal researcher: Enrique Vidal ([email protected]) Department of German Language and Litera- ture Studies (UIBK) from University of Inns- bruck (Austria) Principal researcher: G¤ unter M¤ uhlberger ([email protected]) Computational Intelligence Laboratory (CIL) from National Center for Scientic Research Demokritos (Greece) Principal researcher: Basilis Gatos ([email protected]) Centre for Digital Humanities (UCLDH) from University College London (United Kingdom) Principal researcher: Philip Schoeld ([email protected]) Institute for Dutch Lexicology (INL) (Nether- lands) Principal researcher: Katrien Depuydt ([email protected]) Digital Archives & Repositories Department (ULCC) from University London Computer Centre (United Kingdom) Principal researcher: Richard Davis ([email protected])
Transcript of aims to develop innova- tive, efficient and cost...
Supported by: EU Cultural Heritage:
http://www.transcriptorium.eu
aims to develop innova-tive, efficient and cost-effective solu-tions for the indexing, search and fulltranscription of historical handwrittendocument images, using modern, holis-tic Handwritten Text Recognition tech-nology.
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will turn Handwritten Text Recog-nition (HTR) technology into a mature tech-nology by addressing the following objectives:
1 Enhancing HTR technology for efficient tran-scriptionDeparting from state-of-the-art HTR approaches,
will capitalize on interactive-predictivetechniques for effective and user-friendly computer-assisted transcrition.
2 Bringing the HTR technology to usersExpected users of the HTR technology belong mainlyto two groups: a) individual researchers with expe-rience in handwritten documents transcription inter-ested in transcribing specific documents. b) volun-teers which collaborate in large transcription projects.
3 Integrating the HTR results in public webportalsThe HTR technology will become a support in thedigitization of the handwritten materials. The out-comes of the tools will be attached tothe published handwritten document images. This in-cludes not only full, correct transcriptions, but alsopartially correct transcription and other kinds of auto-matically produced metadata, useful for indexing andsearching.
Project coordinator: Joan Andreu Sanchez([email protected])
Project no.: 600707Start date: 1 January 2013End date: 31 December 2015
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Research groups and institutions:
• Pattern Recognition and Human Language Tech-nology Research Center (PRHLT) from Univer-sitat Politecnica de Valencia (Spain)
Principal researcher: Enrique Vidal([email protected])
• Department of German Language and Litera-ture Studies (UIBK) from University of Inns-bruck (Austria)
Principal researcher: Gunter Muhlberger([email protected])
• Computational Intelligence Laboratory (CIL)from National Center for Scientific Research“Demokritos” (Greece)
Principal researcher: Basilis Gatos([email protected])
• Centre for Digital Humanities (UCLDH) fromUniversity College London (United Kingdom)
Principal researcher: Philip Schofield([email protected])
• Institute for Dutch Lexicology (INL) (Nether-lands)
Principal researcher: Katrien Depuydt([email protected])
• Digital Archives & Repositories Department(ULCC) from University London ComputerCentre (United Kingdom)
Principal researcher: Richard Davis([email protected])
CollectionsE
nglis
hD
utch
Ger
man
Span
ish
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Research results• Document Image Analysis: Pre-processing, image en-
hancing, layout analysis, skew correction, line detection.
• Interactive Handwritten Text Recognition: the
user and the system interact for obtaining the correct transcript.
• Key Word SpottingQuery by string
Query by sample
• Linguistic Resources: language models, lexicon, abbre-
viations.
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Data and tool results
Datasets and ground-truth:• English. Bentham: XVIII/XIX centuries, 80 000
pages, several hands. GT: 800 pages.
• Dutch. Four books: XV century, 2 000 pages, severalhands. GT: 200 pages.
• German. Several collections: from XVI to XX cen-turies, 32 000 pages, several hands. GT: 200 pages.
• Spanish. Plantas: XVII century, 7 000 pages, onehand. GT: 1 000 pages. Esposalles:, from XV to XXcenturies, 291 books, several hands. GT: 2 books.
Tools: DIA, interactive HTR and KWS tools.
