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Journal of Computers
Handwritten signatures are considered as the most natural method of authenticating a person's identity (compared to other biometric and cryptographic forms of authentication). The learning process inherent in Neural Networks (NN) can be applied to the process of verifying handwritten signatures that are electronically captured via a stylus. This paper presents a method for verifying handwritten signatures by using a NN architecture. Various static (e.g., height, slant, etc.) and dynamic (e.g.,doi:10.4304/jcp.3.8.9-22 fatcat:4rchkyxpebflteq6pf2p73bo2q