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Polygon-based image registration: a new approach for geo-referencing historical maps

Yan, Wai Yeung, Easa, Said M., Shaker, Ahmed
Remote sensing letters 2017 v.8 no.7 pp. 703-712
georeferencing, least squares, mathematical models, remote sensing, Ontario
This paper presents a new approach for geo-referencing historical maps using a polygon-based image registration technique. Since most historical maps lack long lasting point features to serve as control primitives for image registration, we explore the use of polygon features as control primitives that can be identified in both the map and the geo-referenced coordinate system based on matching the polygons’ shape context. A coordinate transformation model can be established using the matched vertices of the polygons, and the model coefficients are subsequently estimated using least-squares adjustment. The proposed method was tested on a digitized lithographic map of downtown Toronto, Ontario, Canada, created in 1857. The experimental work showed a good agreement for the image registration where the Dice similarity coefficient was 0.8 (i.e. 80% of overlap found between the two sets of polygons), regardless of using affine or polynomial model.