Character Detection using YOLO for Writer Identification in multiple Medieval books
Alessandra Scotto di Freca, Tiziana D Alessandro, Francesco Fontanella, Filippo Sarria, Claudio De Stefano

TL;DR
This paper explores using the YOLO object detection model to identify scribes in medieval manuscripts by detecting specific characters, improving accuracy over previous template matching and CNN methods.
Contribution
The study introduces YOLO v5 for scribe identification, replacing traditional template matching and CNN, enhancing detection accuracy and enabling reliable writer classification.
Findings
YOLO achieves higher detection accuracy than previous methods.
YOLO confidence scores facilitate rejection thresholds for reliability.
Improved scribe identification in medieval manuscripts.
Abstract
Paleography is the study of ancient and historical handwriting, its key objectives include the dating of manuscripts and understanding the evolution of writing. Estimating when a document was written and tracing the development of scripts and writing styles can be aided by identifying the individual scribes who contributed to a medieval manuscript. Although digital technologies have made significant progress in this field, the general problem remains unsolved and continues to pose open challenges. ... We previously proposed an approach focused on identifying specific letters or abbreviations that characterize each writer. In that study, we considered the letter "a", as it was widely present on all pages of text and highly distinctive, according to the suggestions of expert paleographers. We used template matching techniques to detect the occurrences of the character "a" on each page and…
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Taxonomy
TopicsHandwritten Text Recognition Techniques · Advanced Text Analysis Techniques · Digital Humanities and Scholarship
