Online Signature Recognition Using Artificial Immune Model

This paper presents an approach for online signature recognition which extracts the most commonly used signature features,and utilizes the self-learning and self-adaptation of artificial immune theory to obtain new models with higher distinguishability when the training samples are limited.Experiments show that this approach performs well in sample training and results in satisfactory verification rate and identification rate.