Abstract: Arabic script is inherently cursive, even when machine-printed. When connected to other characters, some Arabic characters may be optionally written in compact aesthetic forms known as ligatures. It is useful to distinguish ligatures from ordinary characters for several applications, especially automatic text recognition. Datasets that do not annotate these ligatures may confuse the recognition system training. Some popular datasets manually annotate ligatures, but no dataset (prior to this work) took ligatures into consideration from the design phase. In this paper, a detailed study of Arabic ligatures and a design for a dataset that considers the representation of ligative and unligative characters are presented. Then, pilot data collection and recognition experiments are conducted on the presented dataset and on another popular dataset of handwritten Arabic words. These experiments show the benefit of annotating ligatures in datasets by reducing error-rates in character recognition tasks.

Yousef Elarian, Irfan Ahmad, Abdelmalek Zidouri and Wasfi G. Al-Khatib, “LUCIDAH Ligative and Unligative Characters in a Dataset for Arabic Handwriting” International Journal of Advanced Computer Science and Applications(IJACSA), 10(8), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100855

@article{Elarian2019,
title = {LUCIDAH Ligative and Unligative Characters in a Dataset for Arabic Handwriting},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2019.0100855},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100855},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {8},
author = {Yousef Elarian and Irfan Ahmad and Abdelmalek Zidouri and Wasfi G. Al-Khatib},
}