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UOHTD: Urdu Offline Handwritten Text Dataset

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Frontiers in Handwriting Recognition (ICFHR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13639))

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Abstract

We present our Offline Urdu Handwritten Text Dataset (UOHTD) in this paper by collecting 800 Urdu handwritten samples written by 800 native language writers. It consists of images in the form of a dataset containing written text samples scanned with multiple spatial resolutions. 8000 text lines and 40000 words as patches have been extracted from sample pages and checked manually and formally using a ground truth database. Machine Learning Tools have been utilized to extract sample pages and segment them into lines and words. Initial trials on demographic (gender and age group) classification of Urdu writers with samples of Offline Urdu Handwritten Text Dataset (UOHTD) has produced promising results (85% for gender and 79% for age group classification) using CNNs. The database would be made available to the researcher worldwide for study into various handwritten-related topics including text recognition, identification of the writer’s age, ethnicity, demographics, gender, and handedness, as well as verification.

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Authors and Affiliations

  1. Foundation University Islamabad, School of Science and Technology, Islamabad, Pakistan

    Aftab Rafique & M. Ishtiaq

Authors
  1. Aftab Rafique
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  2. M. Ishtiaq
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Corresponding author

Correspondence to Aftab Rafique .

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Editors and Affiliations

  1. Walmart Inc., Hoboken, NJ, USA

    Utkarsh Porwal

  2. Universitat Autònoma de Barcelona, Barcelona, Spain

    Alicia Fornés

  3. National University of Sciences and Technology (NUST), Islamabad, Pakistan

    Faisal Shafait

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Rafique, A., Ishtiaq, M. (2022). UOHTD: Urdu Offline Handwritten Text Dataset. In: Porwal, U., Fornés, A., Shafait, F. (eds) Frontiers in Handwriting Recognition. ICFHR 2022. Lecture Notes in Computer Science, vol 13639. Springer, Cham. https://doi.org/10.1007/978-3-031-21648-0_34

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  • DOI: https://doi.org/10.1007/978-3-031-21648-0_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21647-3

  • Online ISBN: 978-3-031-21648-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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