Synthesis of Representative Graphical Symbols by Computing Generalized Median Graph
- 384 Downloads
Median is a general concept of capturing the essential information of a given set of objects. In this work we adopt this concept to the problem of learning, or synthesis, of representative graphical symbols from given examples. Graphical symbols are represented by graphs. This way the learning task is transformed into that of computing the generalized median of a given set of graphs, which is a novel graph matching problem and solved by a genetic algorithm.
KeywordsGenetic Algorithm Edit Distance Input Graph Graph Match Label Graph
Unable to display preview. Download preview PDF.
- 2.D. E. Goldberg, Genetic algorithms in search, optimization and machine learning, Addison-Wesley, 1989. 185Google Scholar
- 3.A. H. Habacha, Structural recognition of disturbed symbols using discrete relaxation, Proc. of 1st Int. Conf. on Document Analysis and Recognition, Saint Malo, France, 170–178, 1991. 183Google Scholar
- 4.A. Hutchinson, Algorithmic Learning, Oxford University Press, 1994. 183Google Scholar
- 5.X. Jiang, A. Münger, and H. Bunke, Computing the generalized median of a set of graphs, Proc. of 2nd ICPAR Workshop on Graph-based Representations, Haindorf, Austria, 115–124, 1999. 183, 185, 187Google Scholar
- 6.R. Kasturi and K. Tmobre (Eds.), Graphics Recognition: Methods and Applications, Springer-Verlag, 1996. 183Google Scholar
- 8.S. Lee, Recognizing hand-written electrical circuit symbols with attributed graph matching, in H. S. Baird, H. Bunke, and K. Yamamoto (Eds.), Structured Document Analysis, 340–358, Springer-Verlag, 1988. 183Google Scholar
- 10.J. Lladós, G. Sánchez, and E. Martí, A string based method to recognize symbols and structural textures in architectural plans, Proc. of 2nd IAPR Workshop on Graphics Recognition, Nancy, France, 287–294, 1997. 183Google Scholar
- 13.A. Münger, Synthesis of prototype graphs from sample graphs, Diploma Thesis, University of Bern, 1998. (in German) 185Google Scholar