@article{(Open Science Index):https://publications.waset.org/pdf/14780,
	  title     = {Syntactic Recognition of Distorted Patterns},
	  author    = {Marek Skomorowski },
	  country	= {},
	  institution	= {},
	  abstract     = {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]).},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {1},
	  number    = {7},
	  year      = {2007},
	  pages     = {2255 - 2259},
	  ee        = {https://publications.waset.org/pdf/14780},
	  url   	= {https://publications.waset.org/vol/7},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 7, 2007},
	}