Abstract
This paper presents an online handwritten benchmark dataset (OHWR-Gurmukhi) for Gurmukhi script. TIET, Patiala released the unconstrained online handwriting databases, OHWR-GNumerals and OHWR-GScript, which contain isolated strokes samples produced by 190 writers. The OHWR-GNumerals covers 10 stroke classes and OHWR-GScript covers 95 stroke classes to represent the Gurmukhi character set. For data collection, two data sets of Gurmukhi words have been finalized after having a consultation with language experts in order to collect the balanced stroke samples. The preprocessing methods used to prepare these datasets include: size normalization, removing duplicate points, interpolating missing points and re-sampling. The purpose of this benchmark is to create a common platform and make the benchmark dataset publically available for research endeavors in the area of online handwriting recognition. The dataset is available as supplement at https://sites.google.com/view/ohwr-gurmukhi-script/.
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Acknowledgment
The authors take this opportunity to thank Technology Development for Indian Languages (TDIL) Programme, Department of Information Technology, Government of India for funding this work.
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Singh, H., Sharma, R.K., Kumar, R., Verma, K., Kumar, R., Kumar, M. (2020). A Benchmark Dataset of Online Handwritten Gurmukhi Script Words and Numerals. In: Nain, N., Vipparthi, S., Raman, B. (eds) Computer Vision and Image Processing. CVIP 2019. Communications in Computer and Information Science, vol 1148. Springer, Singapore. https://doi.org/10.1007/978-981-15-4018-9_41
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