Extracting road vector data from raster maps

Authors:
Yao-Yi Chiang;Craig A. Knoblock
Affiliations:
University of Southern California, Department of Computer Science and Information Sciences Institute, Marina del Rey, CA;University of Southern California, Department of Computer Science and Information Sciences Institute, Marina del Rey, CA
Venue:
GREC'09 Proceedings of the 8th international conference on Graphics recognition: achievements, challenges, and evolution
Year:
2009

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Abstract

Raster maps are an important source of road information. Because of the overlapping map features (e.g., roads and text labels) and the varying image quality, extracting road vector data from raster maps usually requires significant user input to achieve accurate results. In this paper, we present an accurate road vectorization technique that minimizes user input by combining our previous work on extracting road pixels and road-intersection templates to extract accurate road vector data from raster maps. Our approach enables GIS applications to exploit the road information in raster maps for the areas where the road vector data are otherwise not easily accessible, such as the countries of the Middle East. We show that our approach requires minimal user input and achieves an average of 93.2% completeness and 95.6% correctness in an experiment using raster maps from various sources.