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U-DIADS-Bib: a full and few-shot pixel-precise dataset for document layout analysis of ancient manuscripts

  • Special Issue on Visual Pattern Recognition and Extraction for Cultural Heritage
  • Published:
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Abstract

Document Layout Analysis, which is the task of identifying different semantic regions inside of a document page, is a subject of great interest for both computer scientists and humanities scholars as it represents a fundamental step towards further analysis tasks for the former and a powerful tool to improve and facilitate the study of the documents for the latter. However, many of the works currently present in the literature, especially when it comes to the available datasets, fail to meet the needs of both worlds and, in particular, tend to lean towards the needs and common practices of the computer science side, leading to resources that are not representative of the humanities real needs. For this reason, the present paper introduces U-DIADS-Bib, a novel, pixel-precise, non-overlapping and noiseless document layout analysis dataset developed in close collaboration between specialists in the fields of computer vision and humanities. Furthermore, we propose a novel, computer-aided, segmentation pipeline in order to alleviate the burden represented by the time-consuming process of manual annotation, necessary for the generation of the ground truth segmentation maps. Finally, we present a standardized few-shot version of the dataset (U-DIADS-BibFS), with the aim of encouraging the development of models and solutions able to address this task with as few samples as possible, which would allow for more effective use in a real-world scenario, where collecting a large number of segmentations is not always feasible.

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Data availability

The datasets generated and analysed during the current study are available in the U-DIADS-Bib repository.Footnote 6

Notes

  1. Source https://gallica.bnf.fr.

  2. https://gallica.bnf.fr/ark:/12148/btv1b8452767n.

  3. https://gallica.bnf.fr/ark:/12148/btv1b84429190.

  4. https://gallica.bnf.fr/ark:/12148/btv1b85144288.

  5. https://gallica.bnf.fr/ark:/12148/btv1b10527102b.

  6. https://ai4ch.uniud.it/udiadsbib/.

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Acknowledgements

The authors would like to acknowledge the Bibliothèque nationale de France for providing access to the digital library Gallica.

Funding

Partial financial support was received from Piano Nazionale di Ripresa e Resilienza (PNRR) DD 3277 del 30 dicembre 2021 (PNRR Missione 4, Componente 2, Investimento 1.5)—Interconnected Nord-Est Innovation Ecosystem (iNEST).

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Authors and Affiliations

  1. Department of Mathematics, Computer Science and Physics, University of Udine, Udine, Italy

    Silvia Zottin, Axel De Nardin, Claudio Piciarelli & Gian Luca Foresti

  2. Department of Engineering and Architecture, University of Trieste, Trieste, Italy

    Axel De Nardin

  3. Department of Humanities and Cultural Heritage, University of Udine, Udine, Italy

    Emanuela Colombi & Filippo Pavan

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  1. Silvia Zottin
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  2. Axel De Nardin
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Correspondence to Silvia Zottin.

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Zottin, S., De Nardin, A., Colombi, E. et al. U-DIADS-Bib: a full and few-shot pixel-precise dataset for document layout analysis of ancient manuscripts. Neural Comput & Applic (2024). https://doi.org/10.1007/s00521-023-09356-5

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