Introducing an approach for writer recognition based on the i ‐vector paradigm

Abstract

An off-line text-independent writer verification system that leverages the similarities with the field of speaker recognition by employing analogous techniques for modelling and comparing the features extracted from the input text images is presented. The main contribution of this work is the use of the i -vector paradigm in a writer verification setting. The proposed system is evaluated with images of lines of text from the IAM Handwriting Database, and compared with more traditional approaches. The authors also analyse several algorithms for the detection and extraction of points of interest in the text images, different parameters for the modelling part and different scoring techniques. The obtained results show that the use of i -vectors clearly improves the performance of the system even for configurations where the overhead of the additional calculations is minimal.