Signature verification using self-organizing feature map
In this paper we describe the use of the SOFM neural network model for signature verification. The biometric data of all signatures were acquired by a special digital data acquisition pen and fast wavelet transformation was used forfeature extraction. The part of authentic signature data was used for training the SOFM signature verifer. The architecture of the verifer and achieved results are discussed here and ideas for future research are also suggested.