This thesis is an attempt to automate a portion of the paper map conversion process. This includes replacing the manual digitization process by computer assisted skeletonization of scanned paper maps. In colour scanned paper maps various features on the map can be distinguished based on their colour. This research work differs from the previous research in the way that it uses the Delaunay triangulation and the Voronoi diagram to extract 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. Furthermore, map updates are important in any Geographic Information System. This research work can also be used for updates from sources that are either hardcopy maps or digital raster images. The extracted features need manual editing in order to be usable in a Geographic Information System. This involves manual gap filling and clutter removal. A prototype application that is developed as part of the research has been presented. This application requires a digital image as input and processes it to produce skeletons or boundaries of objects. This research work can be further extended by considering automated gap filling in the extracted features.
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