Computer vision & fuzzy logic based offline signature verification and forgery detection

Automated signature verification and forgery detection has many applications in the field of Bank-cheque processing, document authentication, ATM access etc. Handwritten signatures have proved to be important in authenticating a person´s identity, who is signing the document. In this paper a Fuzzy Logic and Artificial Neural Network Based Off-line Signature Verification and Forgery Detection System is presented. As there are unique and important variations in the feature elements of each signature, so in order to match a particular signature with the database, the structural parameters of the signatures along with the local variations in the signature characteristics are used. These characteristics have been used to train the artificial neural network. The system uses the features extracted from the signatures such as centroid, height — width ratio, total area, I^st and II^nd order derivatives, quadrant areas etc. After the verification of the signature the angle features are used in fuzzy logic based system for forgery detection.