Signature Verification based on global features

Biometrics is a verification system that identifies a person based on his physiological and behavioral features. Signature verification is the biometrics identification method which is legally accepted and used in many
commercial fields such as e-business, access control and so on. In this project we proposed a robust offline signature verification based on global features to identify forgeries. In this model prior to extracting the features, we preprocessed the signature in the database. Preprocessing consists of normalization, noise reduction and thinning, for feature set extraction whics consist of global features such as signature
height-to-width ration, height, length, black area, etc.