Syntactic Recognition of Distorted Patterns

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 [1] for a description of patterns. The IE graphs are generated by so-called ETPL(k) graph grammars defined in [1]. An efficient, parsing algorithm for ETPL(k) graph grammars for syntactic recognition of patterns represented by IE graphs has been presented in [1]. In practice, structural descriptions may contain pattern distortions, so that the assignment of a graph g, representing an unknown pattern, to a graph language L(G) generated by an ETPL(k) graph grammar G is rejected by the ETPL(k) type parsing. Therefore, there is a need for constructing effective parsing algorithms for recognition of distorted patterns. The purpose of this paper is to present a new approach to syntactic recognition of distorted patterns. To take into account all variations of a distorted pattern under study, a probabilistic description of the pattern is needed. A random IE graph approach is proposed here for such a description ([2]).

Authors:

• Marek Skomorowski

Keywords:

• Syntactic pattern recognition
• Distorted patterns
• Random graphs
• Graph grammars.

References:

[1] M. Flasiński, On the parsing of deterministic graph languages for
syntactic pattern recognition, Pattern Recognition, 26, 1993, pp. 1-16.
[2] M. Flasiński, M. Skomorowski, Parsing of random graph languages for
automated inspection in statistical-based quality assurance systems,
Machine GRAPHICS & VISION International Journal, 7, 1998,
pp. 565-623.
[3] M. Uliasz, Application of graph grammars for syntactic pattern
recognition of distorted patterns (in Polish), M. S. thesis, Institute of
Computer Science, Jagiellonian University, Krak├│w, Poland, 1999.