Generative Power of Reduction-based Parsable ETPR(k) Graph Grammars for Syntactic Pattern Recognition

2018 ◽  
Vol 12 (2) ◽  
pp. 61-81
Author(s):  
Mariusz Flasiński ◽  
Keyword(s):  
Pattern Recognition ◽  
Graph Grammars ◽  
Syntactic Pattern Recognition ◽  
Generative Power ◽  
Syntactic Pattern

Interpreted Graphs and ETPR(k) Graph Grammar Parsing for Syntactic Pattern Recognition

2019 ◽  
Vol 27 (1) ◽  
pp. 3-19
Author(s):  
Mariusz Flasiński
Keyword(s):  
Pattern Recognition ◽  
Model Theory ◽  
Graph Grammar ◽  
Image Process ◽  
Graph Grammars ◽  
Syntactic Pattern Recognition ◽  
Bottom Up ◽  
Recognition Pattern ◽  
Syntactic Pattern ◽  
Parsing Algorithm

Further results of research into graph grammar parsing for syntactic pattern recognition (Pattern Recognit. 21:623-629, 1988; 23:765-774, 1990; 24:1223-1224, 1991; 26:1-16, 1993; 43:249-2264, 2010; Comput. Vision Graph. Image Process. 47:1-21, 1989; Fundam. Inform. 80:379-413, 2007; Theoret. Comp. Sci. 201:189-231, 1998) are presented in the paper. The notion of interpreted graphs based on Tarski's model theory is introduced. The bottom-up parsing algorithm for ETPR(k) graph grammars is defined.

PATH-CONTROLLED GRAPH GRAMMARS FOR SYNTACTIC PATTERN RECOGNITION

1994 ◽  
Vol 08 (02) ◽  
pp. 485-500
Author(s):  
KUNIO AIZAWA ◽  
AKIRA NAKAMURA
Keyword(s):  
Pattern Recognition ◽  
Graph Structure ◽  
Graph Grammars ◽  
Syntactic Pattern Recognition ◽  
Syntactic Pattern ◽  
Parsing Algorithm

The graph structure is a strong formalism for representing pictures in syntactic pattern recognition. Many models for graph grammars have been proposed as a kind of hyper-dimensional generating systems, whereas the use of such grammars for pattern recognition is relatively infrequent. One of the reasons is the difficulty of building a syntax analyzer for such graph grammars. In this paper, we define a subclass of nPCE graph grammars and present a parsing algorithm of O(n) for both sequential and parallel cases.

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