Abstract
Signature verification is an important research area in the field of personal validation because signatures have become an important and crucial tool for the human identification. The verification of human signature is substantial when dealing with the financial and non-financial transactions. Nowadays, it has become necessary to have a computer-based signature verification system. This helps in verifying the signatures in more convenient way. This paper presents graphical analysis of signatures (original and forged) of human on the basis of simple geometrical features. Artificial neural network has been used as a classifier to distinguish between original and forged signature. Algorithm has been developed, and results have been obtained through MATLAB.
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Saini, P., Uniyal, I., Singh, N. (2018). Offline Graphical Analysis of Signatures Using Geometric Features and Artificial Neural Network. In: Singh, R., Choudhury, S., Gehlot, A. (eds) Intelligent Communication, Control and Devices. Advances in Intelligent Systems and Computing, vol 624. Springer, Singapore. https://doi.org/10.1007/978-981-10-5903-2_112
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DOI: https://doi.org/10.1007/978-981-10-5903-2_112
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