A NEURAL NETWORK APPROACH TO OFF-LINE SIGNATURE VERIFICATION USING DIRECTIONAL PDF

摘要

A neural network approach is proposed to build the first stage of an Automatic Handwritten Signature Verification System. The directional Probability Density Function was used as a global shape factor and its discriminating power was enhanced by reducing its cardinality via filtering. Various experimental protocols were used to implement the backpropagation network (BPN) classifier. A comparison, on the same database and with the same decision rule, shows that the BPN classifier is clearly better than the threshold classifier and compares favourably with the k-Nearest-Neighbour classifier. [References: 27]