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Signature Verification using a "Siamese" Time Delay Neural Network

Authors: Jane Bromley, Isabelle Guyon, Yann LeCun, Eduard Säckinger, Roopak Shah

Published: 1993 (Conference Paper)

Source: Advances in Neural Information Processing Systems

Summary

Abstract

This paper describes an algorithm for verification of signatures written on a pen-input tablet. The algorithm is based on a novel, artificial neural network, called a "Siamese" neural network. This network consists of two identical sub-networks joined at their outputs. During training the two sub-networks extract features from two signatures, while the joining neuron measures the distance between the two feature vectors. Verification consists of comparing an extracted feature vector with a stored feature vector for the signer. Signatures closer to this stored representation than a chosen threshold are accepted, all other signatures are rejected as forgeries.