Abstract
In pattern recognition, median computation is an important technique for capturing the important information of a given set of patterns but it has the main drawback of its exponential complexity. Moreover, the Spectral Graph techniques can be used for the fast computation of the approximate graph matching error, with a considerably reduced execution complexity. In this paper, we merge both methods to define the Median Spectral Graphs. With the use of the Spectral Graph theories, we find good approximations of median graph. Experiments on randomly generated graphs demonstrate that this method works well and it is robust against noise.
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Ferrer, M., Serratosa, F., Sanfeliu, A. (2005). Synthesis of Median Spectral Graph. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492542_18
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DOI: https://doi.org/10.1007/11492542_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26154-4
Online ISBN: 978-3-540-32238-2
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