Abstract
We propose a new method to automatically obtain edit costs for error-tolerant graph matching based on interactive and adaptive graph recognition. Values of edit costs for deleting and inserting nodes and vertices are crucial to obtain good results in the recognition ratio. Nevertheless, these parameters are difficult to be estimated and they are usually set by a naïve trial and error method. Moreover, we wish to seek these costs such that the system obtains the correct labelling between nodes of the input graph and nodes of the model graph. We consider the labelling imposed by a specialist is the correct one, for this reason, we need to present an interactive and adaptive graph recognition method in which there is a human interaction. Results show that when cost values are automatically found, the quality of labelling increases.
This research was partially supported by Consolider Ingenio 2010 and by the CICYT project DPI 2010-17112.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Caetano, T.S., McAuley, J.J., Cheng, L., Le, Q.V., Smola, A.J.: Learning Graph Matching. IEEE Trans. Pattern Anal. Mach. Intell. 31(6), 1048–1058 (2009)
Sanfeliu, A., Fu, K.: A distance measure between attributed relational graphs for pattern recognition. IEEE Trans. on Sys., Man and Cybern. 13, 353–362 (1983)
Bunke, H., Allerman, G.: Inexact graph matching for structural pattern recognition. Pattern Recognition Letters 1(4), 245–253 (1983)
Neuhaus, M., Bunke, H.: A Probabilistic Approach to Learning Costs for Graph Edit Distance. ICPR (3), 389–393 (2004)
Neuhaus, M., Bunke, H.: Self-organizing maps for learning the edit costs in graph matching. IEEE Trans. on Sys., Man, and Cybernetics, Part B 35(3), 503–514 (2005)
Neuhaus, M., Bunke, H.: Automatic learning of cost functions for graph edit distance. Inf. Sci. 177(1), 239–247 (2007)
Bunke, H.: On a relation between graph edit distance and maximum common subgraph. Pattern Recognition Letters 18(8), 689–694 (1997)
Lladós, J., Martí, E., Villanueva, J.J.: Symbol Recognition by Error-Tolerant Subgraph Matching between Region Adjacency Graphs. IEEE Trans. Pattern Anal. Mach. Intell. 23(10), 1137–1143 (2001)
Gold, S., Rangarajan, A.: A Graduated Assignment Algorithm for Graph Matching. IEEE TPAMI 18(4), 377–388 (1996)
Christmas, W.J., Kittler, J., Petrou, M.: Structural matching in computer vision using probabilistic relaxation. IEEE TPAMI 17(8), 749–764 (1995)
Duda, R.O., Hart, P.E.: Pattern Classification and Scene Analysis. J. Wiley, Chichester (1973)
Canny, J.: The future of human-computer interaction. Queue,ACM 4(6), 24–32 (2006)
Vidal, E., Rodríguez, L., Casacuberta, F., García-Varea, I.: Interactive Pattern Recognition. In: MLMI, pp. 60–71 (2007)
Toselli, A.H., Romero, V., Pastor, M., Vidal, E.: Multimodal interactive transcription of text images. Pattern Recognition 43(5), 1814–1825 (2010)
Casacuberta, F., Civera, J., Cubel, E., Lagarda, A.L., Lapalme, G., Macklovitch, E., Vidal, E.: Human interaction for high-quality machine translation. Commun. ACM 52(10), 135–138 (2009)
http://deim.urv.cat/~francesc.serratosa/Tarragona_Graph_Database
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Serratosa, F., Solé-Ribalta, A., Cortés, X. (2011). Automatic Learning of Edit Costs Based on Interactive and Adaptive Graph Recognition. In: Jiang, X., Ferrer, M., Torsello, A. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2011. Lecture Notes in Computer Science, vol 6658. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20844-7_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-20844-7_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20843-0
Online ISBN: 978-3-642-20844-7
eBook Packages: Computer ScienceComputer Science (R0)