A deep learning experiment for semantic segmentation of overlapping characters in palimpsests

التفاصيل البيبلوغرافية
العنوان: A deep learning experiment for semantic segmentation of overlapping characters in palimpsests
المؤلفون: Perino, Michela, Ginolfi, Michele, Felici, Anna Candida, Rosellini, Michela
سنة النشر: 2023
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
الوصف: Palimpsests refer to historical manuscripts where erased writings have been partially covered by the superimposition of a second writing. By employing imaging techniques, e.g., multispectral imaging, it becomes possible to identify features that are imperceptible to the naked eye, including faded and erased inks. When dealing with overlapping inks, Artificial Intelligence techniques can be utilized to disentangle complex nodes of overlapping letters. In this work, we propose deep learning-based semantic segmentation as a method for identifying and segmenting individual letters in overlapping characters. The experiment was conceived as a proof of concept, focusing on the palimpsests of the Ars Grammatica by Prisciano as a case study. Furthermore, caveats and prospects of our approach combined with multispectral imaging are also discussed.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2311.01130
رقم الأكسشن: edsarx.2311.01130
قاعدة البيانات: arXiv