A model of the target object is required for the recognition of cartographic objects in satellite images. We developed a learning system that constructs the structural models for cartographic objects automatically. Using a database of examples extracted from satellite images, this system constructs the abstract model of the object in each class. The images containing the objects are decomposed into primitive figures and are transformed to Attributed Relational Graphs (ARGs) that are very appropriate for the representation of structured data. We generated the object models applying graph-matching algorithms on these graphs. The quality of a model is evaluated by a specific edit-distance of the examples to the model.
We tested our system on images of bridges and roundabouts. We could obtain object models compatible with manually generated models.
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