Abstract
In signature verification, spatio-temporal features offer better performance than the ones extracted from static images. However, estimating spatio-temporal or spatial sequences in static images would be advantageous for recognizers. This paper studies recovered trajectories from skeleton-based images and their impact in automatic signature verification. To this aim, we propose to use a publicly available system for writing order recovery trajectory in offline signatures. Firstly, 8-connected recovered trajectories are generated from our system. Then, we evaluate their impact on the performance of baseline signature verification systems to the original trajectories. Our observations on three databases suggest that verifiers based on distributions are more suitable than those that requiring the exact order of the signatures for the off-2-on challenge.
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Notes
- 1.
By component, we mean a piece of a continuous trajectory without lifting the pen. It is also known as pen-downs or surface trajectories on the literature.
- 2.
Our algorithm is freely available for research purposes at www.github.com/gioelecrispo/wor.
References
Allport, F.H.: Theories of Perception and the Concept of Structure: A Review and Critical Analysis with an Introduction to a Dynamic-Structural Theory of Behavior. Wiley (1955). https://doi.org/10.1037/11116-000
Blankers, V.L., et al.: ICDAR 2009 signature verification competition. In: 10th International Conference on Document Analysis and Recognition, pp. 1403–1407. IEEE (2009). https://doi.org/10.1109/ICDAR.2009.216
Bresenham, J.E.: Algorithm for computer control of a digital plotter. IBM Syst. J. 4(1), 25–30 (1965). https://doi.org/10.1147/sj.41.0025
Crispo, G., Diaz, M., Marcelli, A., Ferrer, M.A.: Tracking the ballistic trajectory in complex and long handwritten signatures. In: 16th International Conference on Frontiers in Handwriting Recognition, pp. 351–356 (2018). https://doi.org/10.1109/ICFHR-2018.2018.00068
De Stefano, C., Garruto, M., Marcelli, A.: A saliency-based multiscale method for on-line cursive handwriting shape description. Int. J. Pattern Recogn. Artif. Intell. 18(6), 1139–1156 (2004). ISSN: 0218-0014
Diaz, M., Ferrer, M.A., Impedovo, D., Malik, M.I., Pirlo, G., Plamondon, R.: A perspective analysis of handwritten signature technology. ACM Comput. Surv. (CSUR) 51(6), 1–39 (2019). https://doi.org/10.1145/3274658
Diaz, M., Ferrer, M.A., Parziale, A., Marcelli, A.: Recovering western on-line signatures from image-based specimens. In: 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), pp. 1204–1209. IEEE (2017). https://doi.org/10.1109/ICDAR.2017.199
Diaz Cabrera, M., Crispo, G., Parziale, A., Marcelli, A., Ferrer Ballester, M.A.: Writing order recovery in complex and long static handwriting. Int. J. Interact. Multimed. Artif. Intell. (2022). In press
Diaz-Cabrera, M., Ferrer, M.A., Morales, A.: Modeling the lexical morphology of western handwritten signatures. PLoS ONE 10(4), 1–22 (2015). https://doi.org/10.1371/journal.pone.0123254
Dijkstra, E.W.: A note on two problems in connexion with graphs. Numer. Math. 1(1), 269–271 (1959). https://doi.org/10.1007/BF01386390
Ferrer, M.A., Diaz, M., Carmona-Duarte, C., Plamondon, R.: Generating off-line and on-line forgeries from on-line genuine signatures. In: 2019 International Carnahan Conference on Security Technology (ICCST), pp. 1–6. IEEE (2019)
Fischer, A., Diaz, M., Plamondon, R., Ferrer, M.A.: Robust score normalization for DTW-based on-line signature verification. In: 2015 13th International Conference on Document Analysis and Recognition (ICDAR), pp. 241–245. IEEE (2015). https://doi.org/10.1109/ICDAR.2015.7333760
Galbally, J., et al.: On-line signature recognition through the combination of real dynamic data and synthetically generated static data. Pattern Recogn. 48(9), 2921–2934 (2015)
Hassaine, A., Al Maadeed, S., Bouridane, A.: ICDAR 2013 competition on handwriting stroke recovery from offline data. In: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR (2013). https://doi.org/10.1109/ICDAR.2013.285
Justino, E.J., El Yacoubi, A., Bortolozzi, F., Sabourin, R.: An off-line signature verification system using HMM and graphometric features. In: Proceedings of the 4th International Workshop on Document Analysis Systems, pp. 211–222. Citeseer (2000)
Kholmatov, A., Yanikoglu, B.: SUSIG: an on-line signature database, associated protocols and benchmark results. Pattern Anal. Appl. 12(3), 227–236 (2009). https://doi.org/10.1007/s10044-008-0118-x
Liwicki, M., et al.: Signature verification competition for online and offline skilled forgeries (SigComp2011). In: 2011 International Conference on Document Analysis and Recognition, pp. 1480–1484 (2011). https://doi.org/10.1109/ICDAR.2011.294
Marcelli, A., Parziale, A., Senatore, R.: Some observations on handwriting from a motor learning perspective. In: 2nd International Workshop on Automated Forensic Handwriting Analysis, pp. 6–10 (2013)
Nguyen, V., Blumenstein, M.: Techniques for static handwriting trajectory recovery: a survey. In: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems, pp. 463–470. ACM (2010). https://doi.org/10.1145/1815330.1815390
Qiao, Y., Nishiara, M., Yasuhara, M.: A framework toward restoration of writing order from single-stroked handwriting image. IEEE Trans. Pattern Anal. Mach. Intell. 28(11), 1724–1737 (2006). https://doi.org/10.1109/TPAMI.2006.216
Sae-Bae, N., Memon, N.: Online signature verification on mobile devices. IEEE Trans. Inf. Forensics Secur. 9(6), 933–947 (2014). https://doi.org/10.1109/TIFS.2014.2316472
Tolosana, R., et al.: SVC-onGoing: signature verification competition. Pattern Recogn. 127, 108609 (2022). https://doi.org/10.1016/j.patcog.2022.108609
Yeung, D.-Y., et al.: SVC2004: first international signature verification competition. In: Zhang, D., Jain, A.K. (eds.) ICBA 2004. LNCS, vol. 3072, pp. 16–22. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-25948-0_3
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Diaz, M., Crispo, G., Parziale, A., Marcelli, A., Ferrer, M.A. (2022). Impact of Writing Order Recovery in Automatic Signature Verification. In: Carmona-Duarte, C., Diaz, M., Ferrer, M.A., Morales, A. (eds) Intertwining Graphonomics with Human Movements. IGS 2022. Lecture Notes in Computer Science, vol 13424. Springer, Cham. https://doi.org/10.1007/978-3-031-19745-1_2
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