Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL’19)
Libraries are digitizing their collections of maps from all eras, generating increasingly large online collections of historical cartographic resources. Aligning such maps to a modern geographic coordinate system greatly increases their utility. This work presents a method for such automatic georeferencing, matching raster image content to GIS vector coordinate data. Given an approximate initial alignment that has already been projected from a spherical geographic coordinate system to a Cartesian map coordinate system, a probabilistic shape-matching scheme determines an optimized match between the GIS contours and ink in the binarized map image. Us- ing an evaluation set of 20 historical maps from states and regions of the U.S., the method reduces average alignment RMSE by 12%.
GIS, georeferencing, historical maps, vector-image alignment
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Licensed to Smith College and distributed CC-BY NC ND under the Smith College Faculty Open Access Policy.
Howe, Nicholas; Weinman, Jerod; Gouwar, John; and Shamji, Aabid, "Details of Deformable Part Models for Automatically Georeferencing Historical Map Images" (2019). Computer Science: Faculty Publications, Smith College, Northampton, MA.