CHI-KNOW-PO

HTR ground-truth of the CHI-KNOW-PO project.

The CHI-KNOW-PO project aims to digitize a corpus of poetic anthologies, commentaries, dictionaries and encyclopedias from the Chinese medieval period (ca. 200-1000) and process them using HTR.

Official page of the htr project

Documentation of the research project

Dataset composition

To date, dataset contains 306 images, for a total of:

• 1.175 TextRegions
• 12.198 TextLines
• 97.523 Glyphs

Images

TBD

Ground-truth specifications

TBD

Informations levels

We provide for each image a pageXML file containing three level of information:

• TextRegion localisation, with a semantic tag (e.g. MainText), following the SegmOnto ontology;
• Baseline localisation and surrounding polygon of the line. Each baseline contains a semantic tag;
• Text.

    <TextRegion id="79718" custom="structure {type:MainText;}">
      <Coords points="2575,4313 2575,2861 2563,1405 219,1413 216,4307 2575,4313"/>
      <TextLine id="870481" custom="structure {type:Text;}">
        <Coords points="2491,1414 2414,1414 2414,1515 2392,1534 2411,1584 2392,1627 2411,1679 2397,1732 2414,1751 2397,2082 2417,2102 2400,2178 2419,2206 2400,2258 2425,2338 2571,2352 2559,1411 2491,1414"/>
        <Baseline points="2492,1415 2504,2327"/>
        <TextEquiv>
          <Unicode>見惡焉其終也已</Unicode>
        </TextEquiv>
      </TextLine>
      <TextLine id="870482" custom="structure {type:Commentary;}">
        <Coords points="2535,2356 2488,2356 2477,2395 2493,2507 2474,2545 2493,2595 2474,2732 2491,2822 2477,2852 2493,2998 2480,3025 2493,3132 2482,3250 2502,3266 2641,3258 2630,2354 2535,2356"/>
        <Baseline points="2536,2359 2552,3267"/>
        <TextEquiv>
          <Unicode>○今案見論語陽</Unicode>
        </TextEquiv>
      </TextLine>

Annotations have been made on the Calfa Vision platform, a free web-based annotation tool for documents and images designed for Oriental scripts.

Some results

TBD

Further readings

TBD

To cite this work

@InProceedings{10.1007/978-3-031-70642-4_3,
author="Bizais-Lillig, Marie
and Vidal-Gor{\`e}ne, Chahan
and Dupin, Boris",
editor="Mouch{\`e}re, Harold
and Zhu, Anna",
title="Optimizing HTR and Reading Order Strategies for Chinese Imperial Editions with Few-Shot Learning",
booktitle="Document Analysis and Recognition -- ICDAR 2024 Workshops",
year="2024",
publisher="Springer Nature Switzerland",
address="Cham",
pages="37--56"
}

Acknowledgments