Signature verification using ART-2 neural network

The ART neural network models have been developed for the clustering of input vectors and have been commonly used as unsupervised learned classifiers. We describe the use of the ART-2 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 for feature extraction. The part of authentic signature data was used for training the ART verifier. The architecture of the verifier and achieved results are discussed and ideas for future research are also suggested.