Abstract
This paper systematically compares two elastic graph matching methods for off-line signature verification: shape-memory snakes and parallel segment matching, respectively. As in many practical applications (i.e. those related to bank environments), the number of sample signatures to train the system must be very reduced, we selected these two methods which hold that property. Both methods also share some other similarities since they use graph models to perform the verification task and require a registration pre-processing. Experimental results on the same database and using the same evaluation metrics have shown that the shape-memory snakes clearly outperformed to the parallel segment matching approach on the same signature dataset (9% EER compared to 24% EER, respectively).
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Vélez, J.F., Sánchez, A., Moreno, A.B., Morillo-Velarde, L. (2011). Comparing Elastic Alignment Algorithms for the Off-Line Signature Verification Problem. In: Ferrández, J.M., Álvarez Sánchez, J.R., de la Paz, F., Toledo, F.J. (eds) New Challenges on Bioinspired Applications. IWINAC 2011. Lecture Notes in Computer Science, vol 6687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21326-7_26
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DOI: https://doi.org/10.1007/978-3-642-21326-7_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21325-0
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