Improved segmentation through dynamic time warping for signature verification using a neural network classifier

A segmentation technique based on dynamic time warping is investigated as a means of obtaining improved alignment between multiple signatures from a writer; the segments generated through this approach are represented by an autoregressive model. The signature verification performance is evaluated with a neural network based classifier, and shown to be a significant improvement over previous results obtained by the authors that were based on uniform segmentation.