A comparison of feature extraction approaches for offline signature verification

This paper proposes two systems for offline signature verification based on a global and on a local approach respectively. The features used consist of different kinds of geometrical, statistical and structural features. For comparison purposes, we used two baseline systems (global and local), both based on a larger number of features encoding the orientations of the strokes using mathematical morphology. Experiments are performed on two offline signature databases, namely DS2-50 and GPDS-104. The obtained results show that we may obtain similar performances even when using a much smaller but more discriminant set of features and that stability of the performance across different databases can be a real challenge.