Handwritten Text Recognition technology and MS Turin, BNU, L.II.14 (T). The “Rescapé’’ case study

The objective of this contribution is to report on the Rescapé project’s experiments in applying HTR technology to the fire-damaged T manuscript. This contribution offers an overview of the creation of the Rescapé dataset and details its compliance with the SegmOnto controlled vocabulary. This case study concentrates on the challenges which fire-damaged manuscripts pose to HTR technology and highlights the effectiveness of resources like YALTAi in optimising the segmentation process. It concludes with a discussion of how the resulting dataset forms a fundamental foundation for future HTR models aimed at analysing damaged medieval manuscripts

Foundation (evidence) · Segmentation · Text recognition · Text segmentation · Digital Humanities and Scholarship · Handwritten Text Recognition Techniques · Image Processing and 3D Reconstruction