A neural network approach for off-line signature verification

We describe methods to analyse and obtain the optimal values of various factors that affect the performance of a signature verification system using a neural network approach. A modified model of backpropagation is used to reduce the learning time of the system. Various factors that are examined in this paper are the effect of learning rate of the neural network, effect of skilled forgeries (computer generated), and effect of preprocessing of images on the accuracy of the system.<>