Abstract
We present a method for finding the stability regions within a set of genuine signatures and for selecting the most suitable one to be used for online signature verification. The definition of stability region builds upon motor learning and adaptation in handwriting generation, while their selection exploits both their ability to model signing habits and their effectiveness in capturing distinctive features. The stability regions represent the core of a signature verification system whose performance is evaluated on a standard benchmark.
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Parziale, A., Fuschetto, S.G., Marcelli, A. (2013). Exploiting Stability Regions for Online Signature Verification. In: Petrosino, A., Maddalena, L., Pala, P. (eds) New Trends in Image Analysis and Processing – ICIAP 2013. ICIAP 2013. Lecture Notes in Computer Science, vol 8158. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41190-8_13
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DOI: https://doi.org/10.1007/978-3-642-41190-8_13
Publisher Name: Springer, Berlin, Heidelberg
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