Syntactic recognition of distorted patterns by means of random graph parsing
In syntactic pattern recognition a pattern can be represented by a graph. Given an unknown pattern represented by a graph g, the problem of recognition is to determine if the graph g belongs to a language L(G) generated by a graph grammar G. The so-called IE graphs have been defined in [Flasi?ski, M., 1993. On the parsing of deterministic graph languages for syntactic pattern recognition. Pattern Recognition 26, 116] for a description of patterns. The IE graphs are generated by so-called ETPL(k) graph grammars defined in (Flasi?ski, 1993). In practice, structural descriptions may contain pattern distortions. For example, because of errors in the primitive extraction process, an IE graph g representing a pattern under study may be distorted, either in primitive properties or in their relations, so that the assignment of the analysed graph g to a graph language L(G) generated by an ETPL(k) graph grammar G is rejected by the ETPL(k) type parsing (Flasi?ski, 1993). Therefore, there is a need for constructing effective parsing algorithms for recognition of distorted patterns, represented by graphs, which is the motivation to do research. The purpose of this paper is to present an idea of a new approach to syntactic recognition of distorted patterns represented by so-called random IE graphs.
distorted patterns random graphs syntactic pattern recognition graph grammars