Document Type
Conference Proceeding
Publication Date
11-2019
Publication Title
Proceedings of 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Abstract
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. Using an evaluation set of 20 historical maps from states and regions of the U.S., the method reduces average alignment RMSE by 12%.
Keywords
GIS, georeferencing, historical maps, vector-image alignment
First Page
5
Last Page
8
DOI
doi.org/10.1145/3347146.3359367
Rights
© 2019 Copyright held by the owner/author(s).
Recommended Citation
Nicholas R. Howe, Jerod Weinman, John Gouwar, and Aabid Shamji. 2019. Deformable Part Models for Automatically Georeferencing Historical Map Images. In Proceedings of 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Chicago, IL, USA, November 5–8, 2019 (SIGSPATIAL ’19), 4 pages. https://doi.org/10.1145/3347146.3359367
Comments
Archived as published. Open access article.