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Erschienen in:
2013 | OriginalPaper | Buchkapitel
An Innovative Character Recognition for Ancient Book and Archival Materials: A Segmentation and Self-learning Based Approach
verfasst von : Nicola Barbuti, Tommaso Caldarola
Erschienen in: Digital Libraries and Archives
Verlag: Springer Berlin Heidelberg
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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).