Punjabi Offline Signature Verification System Using Neural Network

Abstract- The signature identification or verification, means where "identification " implies matching a user signature against a signature associated with the identity that the user claim. Biometrics can be classified into two types Behavioral (signature verification, keystroke dynamics, etc.) and Physiological (iris characteristics, fingerprint, etc.).Signature and Finger Print verifications are most widely used personal verifications and are one of the first few biometrics used even before computers. Signature verification is widely studied and discussed using two approaches. On-line approach and offline approach. Online signature verification represents the dynamic information related to signature which is captured at the time when signature made. The offline signature verification represents the static information of signature. Offline systems are more applicable and easy to use in comparison with on-line systems in many parts of the world however it is considered more difficult than on-line verification due to the lack of dynamic information. This paper presents about offline Signature identification method that had more attraction in recent years because of its necessity for use in daily life routines and when the signature needs to be immediately verified like bank checks, Security for Commercial Transactions, Cheque Authentication, attendance etc. In this paper we present, features types and recent methods used for features extraction in offline signature verification systems.Finally, we suggest new interesting ideas to be incorporated in the future. General Terms Signature verification, Signature matching, biometric Keywords- Signature verification techniques,Preprocessing,feature extraction, feature detection, security. I