Handwritten Signature Authentication using Artificial Neural Networks

Abstract

The main goal of this paper is to describe our research and implementation of a handwritten signature authentication system based on artificial neural networks. In this system the authentication process occurs in the following way: firstly, the users' signatures are read using a pen tablet device and then stored; after that some adjustments in position and scale are accomplished; representative signature features are extracted; the input space dimensionality is reduced using principal component analysis; and finally, the users' signatures are classified as authentic or not, through the use of a neural network. Several experiments were accomplished using a 2440 real signatures database, and the obtained results were very satisfactory.