Presenting actual research questions from academia through publishing datasets is a practice of great importance in order to generate relevant solutions. Therefore, we propose a dataset of handwriting on papyri for the task of writer identification. This dataset is derived directly from research questions in the field of Papyrology, and the samples are selected by experts from the respective field of research. This dataset consists of 50 handwriting samples in Greek on papyri approximately from the 6th century A.D., which belong to 10 different scribes. It is prepared and made freely available for non-commercial research along with their confirmed groundtruth information related to the task of writer identification. This paper presents not only the details of the dataset but also its relation to research questions and how the results of computational analysis can support scholars from manuscript research. Some preprocessing and experimentation results are provided as well in order to highlight the difficulties posed by the image degradation of this dataset.

DIBCO 2019 is the international Competition on Document Image Binarization organized in conjunction with the ICDAR 2019 conference. The general objective of the contest is to identify current advances in document image binarization of machine-printed and handwritten document images using performance evaluation measures that are motivated by document image analysis and recognition requirements. This paper describes the competition details including the evaluation measures used as well as the performance of the 24 submitted methods along with a brief description of each method.