Online Signature Verification for Forgery Detection (T-0702) (MFN 4227)

Abstract

Scientific literature on biometric identity identification and verification dates back to 18th century. However, the development of automated biometric authentication and verification systems is not that much old as it advances with the advancement in computer processing which itself is an emerging area. From the available biometric authentication systems and methods, Handwritten Signature Verification (HSV) systems have taken over as the most emerging and reliable means of authentication/verification. The rising reliance on electronic storage and transmission of documents has raised a need for an online means of electronically verifying the identity of sender/author. This research presents an efficient and robust Online Signature Verification (OSV) system targeting verification rates better than the available state-of-the-art systems in the presence of skilled forgeries. Fourier analysis is employed on the signatures followed by Linear Fisher Discriminant Analysis (LFDA) to obtain compressed (to get lower dimensional) representation while enhancing inter-class scatter between signature patterns. Signature modeling is performed using m-mediod-based modeling approach where m-mediods are put on to represent data distribution in each class. Our mediod-based model is generated in three steps. First, we tend to model the distribution data for each class with m representative mediods upper-bounded by the # of class samples. In the second step, we tend to identify conceivable normality ranges for our mediod-based model through various system parameters tuning. Finally, normality ranges for each identified mediod are identified by exploiting the data distribution around that mediod. Euclidean Distance (ED) is used as dis/similarity. A total of 1560 signature samples including skilled forgeries are considered in our study. The evaluation of the proposed system on Japanese signature dataset provided by SigWiComp2013 realized promising results than the competitors.