Efficient and robust graphics recognition from historical maps

Authors:
Yao-Yi Chiang;Stefan Leyk;Craig A. Knoblock
Affiliations:
Information Sciences Institute and Spatial Sciences Institute, University of Southern California, Marina del Rey, CA;Department of Geography, University of Colorado, Boulder, CO;Department of Computer Science and Information Sciences Institute, University of Southern California, Marina del Rey, CA
Venue:
GREC'11 Proceedings of the 9th international conference on Graphics Recognition: new trends and challenges
Year:
2011

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Abstract

Historical maps contain rich cartographic information, such as road networks, but this information is "locked" in images and inaccessible to a geographic information system (GIS). Manual map digitization requires intensive user effort and cannot handle a large number of maps. Previous approaches for automatic map processing generally require expert knowledge in order to fine-tune parameters of the applied graphics recognition techniques and thus are not readily usable for non-expert users. This paper presents an efficient and effective graphics recognition technique that employs interactive user intervention procedures for processing historical raster maps with limited graphical quality. The interactive procedures are performed on color-segmented preprocessing results and are based on straightforward user training processes, which minimize the required user effort for map digitization. This graphics recognition technique eliminates the need for expert users in digitizing map images and provides opportunities to derive unique data for spatiotemporal research by facilitating time-consuming map digitization efforts. The described technique generated accurate road vector data from a historical map image and reduced the time for manual map digitization by 38%.