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ICDAR 2023 Competition on Indic Handwriting Text Recognition

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Document Analysis and Recognition - ICDAR 2023 (ICDAR 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14188))

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Abstract

This paper presents the competition report on Indic Handwriting Text Recognition (IHTR) held at the 17th International Conference on Document Analysis and Recognition (ICDAR 2023 IHTR). Handwriting text recognition is an essential component for analyzing handwritten documents. Several good recognizers are available for English handwriting text in the literature. In the case of Indic languages, limited work is available due to several challenging factors. (i) Two or more characters are often combined to form conjunct characters, (ii) most Indic scripts have around 100 unique Unicode characters, (iii) diversity in handwriting styles, (iv) varying ink density around the words, (v) challenging layouts with overlap between words and natural unstructured writing, and (vi) datasets with only a limited number of writers and examples.

With this competition, we motivate the researchers to continue researching Indic handwriting text recognition tasks to prevent the risk of vanishing Indic scripts/languages. In this competition, we use a training set of an existing benchmark dataset [3, 4, 6]. We create a new manually annotated validation set and test set for validation and testing purposes. A total of eighteen different teams around the world registered for this competition. Among them, only six teams submitted the results along with algorithm details. The winning team Upstage KR achieves an average 95.94% Character Recognition Rate (CRR) and 88.31% Word Recognition Rate (WRR) over ten languages.

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Notes

  1. 1.

    https://www.ethnologue.com/guides/how-many-languages.

  2. 2.

    The code is available at https://github.com/sanny26/indic-htr.

  3. 3.

    https://www.kaggle.com/competitions/bengaliai-cv19/.

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Acknowledgement

This work is supported by MeitY, Government of India, through the NLTM-Bhashini project.

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Authors and Affiliations

  1. International Institute of Information Technology, Hyderabad, India

    Ajoy Mondal & C. V. Jawahar

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  1. Ajoy Mondal
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  2. C. V. Jawahar
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Correspondence to Ajoy Mondal .

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Editors and Affiliations

  1. TU Dortmund University, Dortmund, Germany

    Gernot A. Fink

  2. Adobe, College Park, MN, USA

    Rajiv Jain

  3. Osaka Metropolitan University, Osaka, Japan

    Koichi Kise

  4. Rochester Institute of Technology, Rochester, NY, USA

    Richard Zanibbi

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Mondal, A., Jawahar, C.V. (2023). ICDAR 2023 Competition on Indic Handwriting Text Recognition. In: Fink, G.A., Jain, R., Kise, K., Zanibbi, R. (eds) Document Analysis and Recognition - ICDAR 2023. ICDAR 2023. Lecture Notes in Computer Science, vol 14188. Springer, Cham. https://doi.org/10.1007/978-3-031-41679-8_25

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  • DOI: https://doi.org/10.1007/978-3-031-41679-8_25

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-41679-8

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