SIGNATURE FORGERY RECOGNITION
Shriganesh Bhandari, Satyam Shukla, Omkar Koyande · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT · 2023
Signatures are one of the most important techniques for biometric authentication. There are two kinds of signature nowadays, offline(static) and dynamic (online). There are greater distinctive characteristics of offline signatures, but there are less distinctive characteristics of offline signatures. Offline signatures are also harder to check. Furthermore, the most significant downside of offline signatures is that even the most talented signer does not sign the same way. This is called Intra-personal variability. Both checking the offline signatures is a difficult problem for researchers. In this research, we proposed an offline signature verification approach based on the Deep Learning to prevent signature fraud by malicious individuals. Index Terms – Offline Signature Recognition, Siamese Neural Network, , Contrastive loss, Euclidean Distance.