Neural Networks Based Signature Recognition

Signature verification technology utilizes the distinctive aspects of the signature to verify the identity of individuals. The technology examines the behavioral components of the signature, such as stroke order, speed and pressure, as opposed to comparing visual images of signatures. Unlike traditional signature comparison technologies, signature verification measures the physical activity of signing. While a system may also leverage a comparison of the visual appearance of a signature, or "static signature," the primary components of signature verification are behavioral. In the last few decades, many approaches have been developed in the pattern recognition area, which approached the off-line signature verification problem. There are two main approaches for off-line signature verification: static approaches and pseudodynamic approaches.