Classification of raster maps for automatic feature extraction
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Strabo: a system for extracting road vector data from raster maps
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Extracting road vector data from raster maps
GREC'09 Proceedings of the 8th international conference on Graphics recognition: achievements, challenges, and evolution
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To exploit the road network in raster maps, the first step is to extract the pixels that constitute the roads and then vectorize the road pixels. Identifying colors that represent roads in raster maps for extracting road pixels is difficult since raster maps often contain numerous colors due to the noise introduced during the processes of image compression and scanning. In this paper, we present an approach that minimizes the required user input for identifying the road colors representing the road network in a raster map. We can then use the identified road colors to extract road pixels from the map. Our approach can be used on scanned and compressed maps that are otherwise difficult to process automatically and tedious to process manually. We tested our approach with 100 maps from a variety of sources, which include 90 scanned maps with various compression levels and 10 computer generated maps. We successfully identified the road colors and extracted the road pixels from all test maps with fewer than four user labels per map on average.