Abstract
In this work we present a hybrid handwritten signature verification system where the on-line reference data acquired through a digitizing tablet serves as the basis for the segmentation process of the corresponding scanned off-line data. Local windows are determined over the image through a self-adjustable learning process and are used to focus the feature extraction step. The positions of the windows are determined according to the complexity of the underlying strokes given by the observation of a handwritten reproduction model. Local feature extraction is bounded by the windows formed and it is used with global primitives to feed the classifier. The overall performance of the system is then measured.
Keywords
- Reference Signature
- Equal Error Rate
- False Acceptance Rate
- Signature Verification
- Feature Extraction Process
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2004 Springer-Verlag Berlin Heidelberg
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Zimmer, A., Ling, L.L. (2004). A Window-Based Hybrid Signature Verification System. In: Zhang, D., Jain, A.K. (eds) Biometric Authentication. ICBA 2004. Lecture Notes in Computer Science, vol 3072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25948-0_77
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DOI: https://doi.org/10.1007/978-3-540-25948-0_77
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22146-3
Online ISBN: 978-3-540-25948-0
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