Parsing of edNLC-graph grammars for scene analysis
Pattern Recognition
A new parsing scheme for plex grammars
Pattern Recognition
Power properties of NLC graph grammars with a polynomial membership problem
Theoretical Computer Science
Handbook of graph grammars and computing by graph transformation: volume I. foundations
Handbook of graph grammars and computing by graph transformation: volume I. foundations
Use of random graph parsing for scene labelling by probabilistic relaxation
Pattern Recognition Letters
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Syntactic algorithm of two-dimensional scene analysis for unmanned flying vehicles
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
Recognition of two-dimensional representation of urban environment for autonomous flying agents
Expert Systems with Applications: An International Journal
| Hi-index | 0.10 |
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 [Flasinski, M., 1993. On the parsing of deterministic graph languages for syntactic pattern recognition. Pattern Recognition 26, 1-16] for a description of patterns. The IE graphs are generated by so-called ETPL(k) graph grammars defined in (Flasinski, 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 (Flasinski, 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.