Abstract
In this paper we focus our research on user identification rather than user verification by analyzing handwritten signature and haptic information such as pressure. For analysis, a multilayer perception (MLP) neural network is adopted. In order to verify the proposed method, 16 users’ signatures were measured with haptic information. We successfully identified users at an average success rate of 81%.
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Alsulaiman, F.A., Cha, J., El Saddik, A. (2008). User Identification Based on Handwritten Signatures with Haptic Information. In: Ferre, M. (eds) Haptics: Perception, Devices and Scenarios. EuroHaptics 2008. Lecture Notes in Computer Science, vol 5024. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69057-3_12
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DOI: https://doi.org/10.1007/978-3-540-69057-3_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69056-6
Online ISBN: 978-3-540-69057-3
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