Automatic interpretation of scanned topographic maps: A raster-based approach

Abstract

This paper presents results of an ongoing project in the field of pattern recognition and automatic vectorization. The goal is to obtain multiple information and structured objects from digital topographic maps in raster format using an automated process. An approach of knowledge-based Template Matching with high recognition rates (about 95%) and a procedure to segment and isolate coherent areas of a colour layer are presented. All segmented areas are encoded uniquely, which allows the calculation of features for every area. The segmentation and the features can serve as a preselection in the raster image to obtain information about regions or objects of high, low or no interest. Furthermore, a new procedure that provides an automatic vectorization of areal objects is shown. The vectorization occurs by adjusting the end points of straight line segments, facilitated by robust estimation functions which are resistant to falsely assigned parts of areal objects and stable with respect to deviation from the given distributional model. The resulting data can be exported as DXF to standard CAD-packages or GIS-Systems for further use. The methods presented have been tested in many topographic maps and found to be operationally and qualitatively suitable for automatic processing.