Dynamic signature is behavioural biometric attribute which is commonly used to identity verification. Methods based on the partitioning are one of the types of methods for identity verification using signature biometric attribute. These methods divide trajectories of the signature into parts and during verification phase compare created fragments of trajectories in each partition. Partitioning is performed on the basis of values of signals describing dynamics of signing process (e.g. pen velocity or pen pressure). In this paper we propose a new method for dynamic signature verification using hybrid partitioning. Partitions in the proposed method can be interpreted as, for example, high velocity in the first phase of the signing process or low pressure in the final phase of the signing process. Our method assumes use of all partitions during classification process and our classifier is based on the flexible neuro-fuzzy system of the Mamdani type. Simulations were performed using public SVC2004 dynamic signature database.
展开▼
