Abstract
This paper presents a preliminary easy to explain and effective framework for supporting dynamic signature analysis in forensic settings. The proposed approach is based on measuring similarities among signatures by applying Dynamic Time Warping on easy to derive dynamic measures. The long term goal of our research is to provide forensic handwriting examiners with a decision support tool to perform reproducible and less questionable inference.
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Mazzolini, D., Pavan, P., Pirlo, G., Vessio, G. (2020). Towards a Decision Support Framework for Forensic Analysis of Dynamic Signatures. In: Ceci, M., Ferilli, S., Poggi, A. (eds) Digital Libraries: The Era of Big Data and Data Science. IRCDL 2020. Communications in Computer and Information Science, vol 1177. Springer, Cham. https://doi.org/10.1007/978-3-030-39905-4_2
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DOI: https://doi.org/10.1007/978-3-030-39905-4_2
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