TextBite: A Historical Czech Document Dataset for Logical Page Segmentation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F26%3A0197678" target="_blank" >RIV/00216305:26230/26:0197678 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-032-09368-4_8" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-032-09368-4_8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-032-09368-4_8" target="_blank" >10.1007/978-3-032-09368-4_8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

TextBite: A Historical Czech Document Dataset for Logical Page Segmentation

Popis výsledku v původním jazyce

Logical page segmentation is an important step in document analysis, enabling better semantic representations, information retrieval, and text understanding. Previous approaches define logical segmenta- tion either through text or geometric objects, relying on OCR or precise geometry. To avoid the need for OCR, we define the task purely as seg- mentation in the image domain. Furthermore, to ensure the evaluation remains unaffected by geometrical variations that do not impact text segmentation, we propose to use only foreground text pixels in the eval- uation metric and disregard all background pixels. To support research in logical document segmentation, we introduce TextBite, a dataset of historical Czech documents spanning the 18th to 20th centuries, fea- turing diverse layouts from newspapers, dictionaries, and handwritten records. The dataset comprises 8,449 page images with 78,863 annotated segments of logically and thematically coherent text. We propose a set of baseline methods combining text region detection and relation predic- tion. The dataset, baselines and evaluation framework can be accessed at https://github.com/DCGM/textbite-dataset.

Název v anglickém jazyce

TextBite: A Historical Czech Document Dataset for Logical Page Segmentation

Popis výsledku anglicky

Logical page segmentation is an important step in document analysis, enabling better semantic representations, information retrieval, and text understanding. Previous approaches define logical segmenta- tion either through text or geometric objects, relying on OCR or precise geometry. To avoid the need for OCR, we define the task purely as seg- mentation in the image domain. Furthermore, to ensure the evaluation remains unaffected by geometrical variations that do not impact text segmentation, we propose to use only foreground text pixels in the eval- uation metric and disregard all background pixels. To support research in logical document segmentation, we introduce TextBite, a dataset of historical Czech documents spanning the 18th to 20th centuries, fea- turing diverse layouts from newspapers, dictionaries, and handwritten records. The dataset comprises 8,449 page images with 78,863 annotated segments of logically and thematically coherent text. We propose a set of baseline methods combining text region detection and relation predic- tion. The dataset, baselines and evaluation framework can be accessed at https://github.com/DCGM/textbite-dataset.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/DH23P03OVV060" target="_blank" >DH23P03OVV060: semANT – Sémantický průzkumník textového kulturního dědictví</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Document Analysis and Recognition – ICDAR 2025 Workshops

ISBN

978-3-032-09367-7

ISSN

—

e-ISSN

—

Počet stran výsledku

17

Strana od-do

124-140

Název nakladatele

Springer Nature Switzerland

Místo vydání

Cham

Místo konání akce

Wuhan, Čína

Datum konání akce

16. 9. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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