OCR analysis for the hand-printed books from the 18th century | Ari Vesalainen | #TUC22
Channel: Transkribus
Date: 2022-10-05

Scholarship presentation by Ari Vesalainen, University of Helsinki
Fine-grained OCR document layout analysis for the hand-printed books from the 18th century using Transkribus: accuracy and challenges
Modern Computer vision methods in object recognition, especially different image segmentation methods, can be used for document layout analysis. Most of the current OCR systems focus only on detecting text regions and extracting text lines; however, these are not capable of separating different page element types (e.g., paragraphs, marginalia, headers). 
The thesis analyzes and compares how image segmentation methods are used for fine-grained OCR Document Layout Analysis. The research question is to study how accurately layout analysis can detect different page-level elements from printed 18th-century material and is the accuracy enough for research purposes. 
The analysis covers two models, one using Semantic Segmentation (P2PaLA in Transkribus) and another using Instance Segmentation (Mask R-CNN). In addition, a comparison of the performance differences between these implementations is provided. The dataset includes 600 pages of fine-grained labeled images from four different editions of David Hume’s History of England from 1754, 1759, 1762, and 1778.