## Signature analysis system using a convolutional neural network

### Alicja Winnicka, Karolina Kęsik, Dawid Połap

DOI: http://dx.doi.org/10.15439/2019F28

Citation: Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 18, pages 287–290 (2019)

Abstract. Identity verification using biometric methods has been used for many years. A special case is a handwritten signature made on a digital device or piece of paper. For the digital analysis and verification of its authenticity, special methods are needed. Unfortunately, this is a rather complicated task that quite often requires complex processing techniques. In this paper, we propose a system of signatures verification consisting of two stages. In the first one, a signature pattern is created. Thanks to this, the first attempt to verify identity takes place. In the case of approval, the second stage is followed by the processing of a graphic sample containing a signature by the convolutional neural network. The proposed technique has been described, tested and discussed due to its practical use.

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