A dataset of seals in Arabic manuscripts has been created for the task of pattern detection from the publicly available images of the “Staatsbibliothek zu Berlin” here. Only seals with a minimum of 4 occurrences in different images have been selected, resulting in 8 different seals and 77 images in total.

The dataset has been split into three sub-sets (train, validation, test) in order to follow the standard procedure followed by modern deep-learning models. Furthermore, each image has one corresponding ".xml" file containing the annotation information of seals in that image using the Pascal Voc format.

The research for this work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC 2176 ‘Understanding Written Artefacts: Material, Interaction and Transmission in Manuscript Cultures', project no. 390893796. The research was conducted within the scope of the Centre for the Study of Manuscript Cultures (CSMC) at Universität Hamburg.

In addition, we thank Aneta Yotova for annotating the samples in this dataset.