Spectral Median Graphs Applied to Graphical Symbol Recognition

  • Miquel Ferrer
  • Ernest Valveny
  • Francesc Serratosa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4225)

Abstract

Generalized median graph is a general concept useful to capture the essential information of a set of graphs. In addition, spectral techniques can be used to obtain approximate solutions of graph matching problems in a reasonable time. In this work we use the novel concept of spectral median graph which takes advantage of both the median concept and the spectral techniques, to synthesize the representative of a set of graphical symbols. The results show that this concept represents appropriately the most important intra-class features, while rejecting small distortions and, for extension, it can be used to infer a prototype of a set of symbols.

References

  1. 1.
    Ullman, J.R.: An algorithm for subgraph isomorphism. Journal of ACM 23(1), 31–42 (1976)MATHCrossRefGoogle Scholar
  2. 2.
    Bunke, H., Messmer, B.T.: Recent advances in graph matching. IJPRAI 11(1), 169–203 (1997)Google Scholar
  3. 3.
    Jiang, X., Münger, A., Bunke, H.: On median graphs: Properties, algorithms, and applications. IEEE Trans. Pattern Anal. Mach. Intell. 23(10), 1144–1151 (2001)CrossRefGoogle Scholar
  4. 4.
    Jiang, X., Münger, A., Bunke, H.: Synthesis of representative graphical symbols by computing generalized median graph. In: Chhabra, A.K., Dori, D. (eds.) GREC 1999. LNCS, vol. 1941, pp. 183–192. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  5. 5.
    Umeyama, S.: An eigendecomposition approach to weighted graph matching problems. IEEE Transactions on Pattern Recognition and Image Analysis 10(5), 695–703 (1988)MATHGoogle Scholar
  6. 6.
    Ferrer, M., Serratosa, F., Sanfeliu, A.: Synthesis of median spectral graph. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds.) IbPRIA 2005. LNCS, vol. 3523, pp. 139–146. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  7. 7.
    Lladós, J., Valveny, E., Sánchez, G., Martí, E.: Symbol Recognition: Current Advances and Perspectives. In: Blostein, D., Kwon, Y.-B. (eds.) GREC 2001. LNCS, vol. 2390, pp. 104–127. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  8. 8.
    Gold, S., Rangarajan, A.: A graduated assignment algorithm for graph matching. IEEE Trans. Pattern Anal. Mach. Intell. 18(4), 377–388 (1996)CrossRefGoogle Scholar
  9. 9.
    Sanfeliu, A., Fu, K.: A distance measure between attributed relational graphs for pattern recognition. IEEE Transactions on Systems, Man and Cybernetics 13(3), 353–362 (1983)MATHGoogle Scholar
  10. 10.
    Dosch, P., Valveny, E.: Report on the second symbol recognition contest (to appear in lncs series) (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Miquel Ferrer
    • 1
  • Ernest Valveny
    • 1
  • Francesc Serratosa
    • 2
  1. 1.Computer Vision Center, Dep. Ciències de la ComputacióUniversitat Autònoma de BarcelonaBellaterraSpain
  2. 2.Departament d’Enginyeria Informàtica i MatemàtiquesUniversitat Rovira i VirgiliTarragonaSpain

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