Abstract
Automated delineation of linear cultural structures can help to improve the classification of remotely-sensed images. This topic also provides an excellent testbed for knowledge-based computer vision research. In this paper, a road network extraction system, useful on SPOT satellite images, is described. By applying semantic model-fitting operators, an initial spatial segmentation is obtained. To analyse the resulting primal road network, declaratively stated knowledge about generic appearances of roads and crossroads on SPOT images is used. As a result a more detailed description of the network can be obtained. Advantages and drawbacks of the use of existing knowledge base tools for this computer vision task are reported.
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