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An Innovative Character Recognition for Ancient Book and Archival Materials: A Segmentation and Self-learning Based Approach

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Digital Libraries and Archives (IRCDL 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 354))

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Abstract

The paper illustrates the invention of a method and an apparatus able to recognize the text in a set of digital images referring to pages of ancient manuscripts or printed books. It includes the following macro steps: identifying and connecting in sequence regions containing words in a subset of the images; structuring a thesaurus of fonts used in those regions; performing the character recognition of one or more images belonging to the set, associating to this recognition a first value of efficiency. The prototype is patent pending (National Pat. Pend. n. BA2011A000038 – Intern. Pat. Pend. n. I116-PCT).

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Author information

Authors and Affiliations

  1. Department of Classical and Late Antiquity Studies, University of Bari Aldo Moro, Italy

    Nicola Barbuti

  2. D.A.BI.MUS. L.L.C., Spin Off of University of Bari Aldo Moro, Italy

    Tommaso Caldarola

Authors
  1. Nicola Barbuti
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  2. Tommaso Caldarola
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Editor information

Editors and Affiliations

  1. Department of Information Engineering, University of Padua, Via Gradenigo, 6/a, 35131, Padua, Italy

    Maristella Agosti  & Nicola Ferro  & 

  2. Department of Computer Science, University of Bari, Via E. Orabona, 4, 70126, Bari, Italy

    Floriana Esposito  & Stefano Ferilli  & 

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Barbuti, N., Caldarola, T. (2013). An Innovative Character Recognition for Ancient Book and Archival Materials: A Segmentation and Self-learning Based Approach. In: Agosti, M., Esposito, F., Ferilli, S., Ferro, N. (eds) Digital Libraries and Archives. IRCDL 2012. Communications in Computer and Information Science, vol 354. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35834-0_26

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  • DOI: https://doi.org/10.1007/978-3-642-35834-0_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35833-3

  • Online ISBN: 978-3-642-35834-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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