Old maps are more than a cultural artefact: they are data. Data about the past still hold value for science and decision-making today. Libraries and archives have come a long way in digitising their inventories of thousands, sometimes millions, of historical maps using high-resolution scanning. Unfortunately, even with digital images the rich spatial and semantic information is inaccessible for people without a strong background in history and cartography. Only with georeferencing can historical maps be used in GIS and thus processed and compared with modern geospatial data. We introduce content-based image retrieval to automatically localise and georeference map images from topographic map series. We align the maps by extracting a subset of their symbols and cross-referencing them with online reference data from OpenStreetMap. We demonstrate our method with the Karte des Deutschen Reiches at 1: 100,000 scale, obtaining 96% correct location predictions and a median georeferencing error of 101 m.