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Making Large Collections of Handwritten Material Easily Accessible and Searchable

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Digital Libraries: Supporting Open Science (IRCDL 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 988))

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Abstract

Libraries and cultural organisations contain a rich amount of digitised historical handwritten material in the form of scanned images. A vast majority of this material has not been transcribed yet, owing to technological challenges and lack of expertise. This renders the task of making these historical collections available for public access challenging, especially in performing a simple text search across the collection. Machine learning based methods for handwritten text recognition are gaining importance these days, which require huge amount of pre-transcribed texts for training the system. However, it is impractical to have access to several thousands of pre-transcribed documents due to adversities transcribers face. Therefore, this paper presents a training-free word spotting algorithm as an alternative for handwritten text transcription, where case studies on Alvin (Swedish repository) and Clavius on the Web are presented. The main focus of this work is on discussing prospects of making materials in the Alvin platform and Clavius on the Web easily searchable using a word spotting based handwritten text recognition system.

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Acknowledgment

This work was supported by the Swedish strategic research programme eSSENCE and the Riksbankens Jubileumsfond (Dnr NHS14-2068:1).

Author information

Authors and Affiliations

  1. Department of Information Technology, Uppsala University, Uppsala, Sweden

    Anders Hast & Ekta Vats

  2. University Library, Uppsala University, Uppsala, Sweden

    Per Cullhed

  3. Institute of Informatics and Telematics, CNR, Pisa, Italy

    Matteo Abrate

Authors
  1. Anders Hast
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  2. Per Cullhed
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  3. Ekta Vats
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  4. Matteo Abrate
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Corresponding author

Correspondence to Anders Hast .

Editor information

Editors and Affiliations

  1. Italian National Research Council, Pisa, Italy

    Paolo Manghi

  2. Italian National Research Council, Pisa, Italy

    Leonardo Candela

  3. University of Padua, Padua, Italy

    Gianmaria Silvello

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Hast, A., Cullhed, P., Vats, E., Abrate, M. (2019). Making Large Collections of Handwritten Material Easily Accessible and Searchable. In: Manghi, P., Candela, L., Silvello, G. (eds) Digital Libraries: Supporting Open Science. IRCDL 2019. Communications in Computer and Information Science, vol 988. Springer, Cham. https://doi.org/10.1007/978-3-030-11226-4_2

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  • DOI: https://doi.org/10.1007/978-3-030-11226-4_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11225-7

  • Online ISBN: 978-3-030-11226-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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