Description:
While historical newspapers recently have gained a lot of attention in the digital humanities, transforming them into machine-readable data by means of OCR poses some major challenges. In orderto address these challenges, we have developed an end-to-end OCR pipeline named Origami. Thispipeline is part of a current project on the digitization and quantitative analysis of the Germannewspaper “Berliner Börsen-Zeitung” (BBZ), from 1872 to 1931. The Origami pipeline reuses existing open source OCR components and on top offers a new configurable architecture for layoutdetection, a simple table recognition, a two-stage X-Y cut for reading order detection, and a newrobust implementation for document dewarping. In this paper we describe the different stages of theworkflow and discuss how they meet the above-mentioned challenges posed by historical newspapers.