From map images to geographic names

Map labels provide valuable geographic information by an-notating geographic phenomenona with text descriptions. However, many interesting and useful maps are only avail-able as images and hence this information is not readily ac-cessible in a Geographic Information System (GIS). Previous work on text recognition in maps considers maps as a spe-cial type of image to be processed using Optical Character Recognition (OCR) techniques and does not pay attention to the typical workflows in a GIS. As a result, to convert map labels into machine-readable text, a user has to switch between OCR and GIS software, transform the detected text locations from the image coordinates (in OCR) to the map coordinates (in GIS), and apply data import/export proce-dures. This tedious process limits the opportunity to access text information in maps. This paper presents ArcStrabo, an integration of our previous text recognition work and a GIS, which uses a GIS user interface, workflows, and data types to enable efficient training of text recognition algo-rithms for converting map labels to a table of geographic names. We show that ArcStrabo facilitates map digitiza-tion processes, eliminates the need for GIS users to learn additional OCR tools, and does not require manual data ex-port/import procedures between GIS and OCR software.