DocumentCode
2602695
Title
Graph Classification Using Genetic Algorithm and Graph Probing Application to Symbol Recognition
Author
Barbu, Eugen ; Raveaux, Romain ; Locteau, Herve ; Adam, Sebastien ; Heroux, Pierre ; Trupin, Eric
Author_Institution
LITIS Labs, Rouen Univ.
Volume
3
fYear
0
fDate
0-0 0
Firstpage
296
Lastpage
299
Abstract
We present in this paper a graph classification approach using genetic algorithm and a fast dissimilarity measure between graphs called graph probing. The approach consists in the learning of a set of synthetic graph prototypes which are used for a 1NN classification step. Some experiments are performed on real data sets, representing 10 symbols. These tests demonstrate the interest to produce prototypes instead of finding representatives which simply belong to the data set
Keywords
genetic algorithms; graph theory; image recognition; neural nets; pattern classification; genetic algorithm; graph classification; graph probing application; symbol recognition; synthetic graph prototypes; Classification algorithms; Context modeling; Genetic algorithms; Image databases; Image representation; Noise generators; Pattern recognition; Prototypes; Spatial databases; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location
Hong Kong
ISSN
1051-4651
Print_ISBN
0-7695-2521-0
Type
conf
DOI
10.1109/ICPR.2006.612
Filename
1699524
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