The field of document recognition in the cultural heritage is rapidly progressing, wherein vast amounts of ancient manuscripts in libraries and other institutions across the world are increasingly undergoing digitisation and transcription. However, the automatic recognition of patterns in ancient manuscripts to render them readable, searchable and understandable remains a challenging task. This can be due to degradations including ink bleed-through, ink corrosion, stains on paper or parchment, difficulty in the character discrimination, elements different from the text, such as images, etc. that limit the effectiveness of existing techniques. In recent times, machine learning, and deep learning-based methods in particular, have achieved significant performance improvements in document recognition. The aim of this Special Issue is to present recent advances in methods and applications
for document recognition in the cultural heritage, attracting research papers from a wide array of disciplines, including machine learning, pattern recognition, image analysis, and digital humanities.
Topics include, but are not limited to, the following:
-Handwritten document analysis
-Text line extraction or segmentation
-Document image binarization
-Background noise removal
-Automatic recognition and transcription of manuscripts
-Active learning for handwritten text recognition
-Dating of historical manuscripts
-Document layout analysis
-Feature extraction and representation
-Digital humanities applications
-Image processing, classification, and retrieval
Deadline for manuscript submissions: 31 July 2022. For more information contact Prof. Dr. Alessia Amelio.