This work presents a methodology to automate some parts of the manual digitization process. This includes replacing the manual digitization process by computer assisted skeletonization using scanned paper maps. In colour scanned paper maps various features on the map can be distinguished based on their colour. This research work utilizes the Delaunay triangulation and the Voronoi diagram in order to extract the skeletons that are guaranteed to be topologically correct. The features thus extracted as object centrelines can be stored as vector maps in a Geographic Information System after labelling and editing.
O. Sharma, F. Anton, and D. Mioc, “On the isomorphism between the medial axis and a dual of the Delaunay graph,” in International Symposium Voronoi Diagrams in Science and Engineering (ISVD), 2009, pp. 89-95.
C. M. Gold, D. Mioc, F. Anton, O. Sharma, and M. Dakowicz, “A methodology for automated cartographic data input, drawing and editing using kinetic Delaunay/Voronoi diagrams,” in Generalized Voronoi Diagram: A Geometry-Based Approach to Computational Intelligence, Springer Berlin Heidelberg, 2008, pp. 159-196.
O. Sharma, D. Mioc, and F. Anton, “Feature Extraction and Simplification from colour images based on Colour Image Segmentation and Skeletonization using the Quad-Edge data structure,” in International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG), 2007, pp. 225-232.
O. Sharma, D. Mioc, and F. Anton, “Voronoi diagram based automated skeleton extraction from colour scanned maps,” in International Symposium Voronoi Diagrams in Science and Engineering (ISVD), 2006, pp. 186-195.