Can Signature Biometrics Address Both Identification and Verification Problems?

Handwritten signatures are one of the most socially acceptable and traditionally used person identification and authentication metric. Although a number of authentication systems based on handwritten signatures have been proposed, a little attention is paid towards employing signatures for person identification. In this work, we address both the identification and verification problems related to analysis of dynamic handwritten signatures. In this way, the need to present username before biometric verification can be eliminated in current signature based biometric authentication systems. A compressed sensing approach is used for user identification and to reject a query signature that does not belong to any user in the database. Once a person is identified, an automatic alignment of query signature with the reference template is carried out such that the correlations between two signature instances are maximized. An elastic distance matching algorithm is then run over the presented data which declares the query signature as either genuine or forged based on the dissimilarity with the reference signature. Our results show that dynamic signatures can be accurately used for person identification along with the traditional verification methods.