From Detection to Modelling: An End-to-End Paleographic System for Analysing Historical Handwriting Styles

Handwriting analysis in historical documents, crucial for paleography, includes both macroscopic and microscopic examinations. It ranges from assessing the general visual patterns of pages to detailed studies of individual letters. Such analysis not only aids in dating documents and identifying scribes but also provides insights into the evolution of handwriting styles and offers a comprehensive view of historical writing practices. This work proposes a novel end-to-end paleographic system designed for automated handwriting analysis, consisting of three main components: automatic detection and recognition of letters, contrastive hierarchical clustering of the detected letters, and the creation of representative models for the samples in each cluster. These models provide a visual representation of the style variations for each letter. This system processes full manuscript page images to model the diverse shapes of each letter, capturing the inherent variability in historical handwriting styles. The performance of each of the three main system components has been evaluated on a dataset of Greek letters on papyri, achieving results comparable to the state of the art across all three components.