Automatic Learning of Symbol Descriptions Avoiding Topological Ambiguities ∗

In this paper we address both automatic recognition of sketched symbols and the construction of the corresponding models from user drawn examples. Our approach is based on a two stage process. In a rst phase we use an Adjacency Grammar to express topological properties of the symbol. In order to be able to further disambiguate topologically similar con gurations on the rules of the grammar that are triggered by the recognition process produce a set of local geometric invariants is de ned. The combination of both steps results in an e cient recognition method for user drawn sketches. Furthermore, we show that the same approach can easily be adapted for the generation of Adjacency Grammars from user provided and hand drawn examples.