Presents a method for the recognition of symbols on binary images, especially tailored for geographic maps. The prototyping stage is performed by means of a geometric approach: using a suitable distance definition, the prototype of a class is obtained as the pattern minimizing the sum of distances among itself and all the samples of the considered class. In this phase some statistical parameters characterizing the distortions occurring on the symbols are also obtained, so allowing the estimate of the recognition reliability. On the basis of the misclassification and reject costs, some tuning parameters, affecting the classification criteria, are also evaluated in order to maximize the classification performances. Experimental results for several test maps are finally presented.
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