The problem of extracting distinct map symbols from raster maps will be addressed in this paper. To enable natural scientists to analyse the nation-wide distribution of natural objects such as avalanche obstructions, dry channels, tree groups, a semi-automatic method has been developed to detect specific symbols from scanned topographic maps. The Swiss Federal Institute of Forest Snow And Landscape Research (WSL) uses the published map scale 1 :25 '000 of the Swiss Federal Office of Topography (L+ T).
After labelling and tracing the binarised raster data, shape descriptors like area, perimeter, moments, elongation, eccentricity, skeletons, Euler number and Fourier descriptors are calculated and stored in an image symbol database. In an interactive process, the user defines the best fitting discrimination parameters based on the shape descriptor values. A local Hough transformation improves the detection rate for line symbols such as found for avalanche obstacles.
Shape descriptors allow to identify map symbols like single trees, observation towers and triangulation. To detect complex map symbols such as dry channels or avalanche obstacles, a distance-weighted triangulation is used to build a tetrahedron-like data structure called tetra-tree. The tetra-tree allows to analyse and classify the spatial distribution of the primitives found with shape descriptors. Generalised orientation and the convex hull of complex map symbols can be calculated directly from tetra-trees.
Some implementation details and generic limitations will be discussed.