Abstract
Stroke reconstruction from offline handwriting is an important research field. This article presents Online Signal Restoration (OSR) using Arabic Handwriting Dhad Dataset competition organized at ASAR 2021. The goal of this competition is to collect different systems and compare recent advances in online handwriting recovery. This competition has attracted 4 teams from Regim lab. The participating systems were evaluated on known data and tested on unknown dataset. The evaluation metrics are based on Root Mean Squared Error (RMSE), Euclidean Distance (ED) and visual comparison of the recovered velocity. This paper details the proposed competition by describing the used dataset, the participating systems and their effectiveness based on the evaluation metrics.
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Acknowledgements
The research leading to these results has received funding from the Ministry of Higher Education and Scientific Research of Tunisia under the grant agreement number LR11ES4.
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Rabhi, B., Elbaati, A., Hamdani, T.M., Alimi, A.M. (2021). ASAR 2021 Competition on Online Signal Restoration Using Arabic Handwriting Dhad Dataset. In: Barney Smith, E.H., Pal, U. (eds) Document Analysis and Recognition – ICDAR 2021 Workshops. ICDAR 2021. Lecture Notes in Computer Science(), vol 12916. Springer, Cham. https://doi.org/10.1007/978-3-030-86198-8_26
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DOI: https://doi.org/10.1007/978-3-030-86198-8_26
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