Authors:
Mahdi Jampour
;
Hussein Mohammed
and
Jost Gippert
Affiliation:
Cluster of Excellence, Understanding Written Artefacts, Universität Hamburg, Hamburg, Germany
Keyword(s):
Generative AI, Inpainting, Deep CNN, Historical Manuscripts, Image Enhancement, Palimpsests.
Abstract:
Palimpsests are manuscripts that have been scraped or washed for reuse, usually as another document. Recovering the undertext of these manuscripts can be of significant interest to scholars in the humanities. Multispectral imaging is a technique often used to make the undertext visible in palimpsests. Nevertheless, this approach is not sufficient in many cases, due to the fact that the undertext in resulting images is still covered by the overtext or other artefacts. Therefore, we propose defining this issue as an inpainting problem and enhancing the readability of the undertext using generative image inpainting. To this end, we introduce a novel method for generating synthetic multispectral palimpsest images and make the generated dataset publicly available. Furthermore, we utilise this dataset in the fine-tuning of a generative inpainting approach to enhance the readability of palimpsest undertext. The evaluation of our approach is provided for both the synthetic dataset and palimp
sests from actual research in the humanities. The evaluation results indicate the effectiveness of our method in terms of both quantitative and qualitative measures.
(More)