State-of-the-art in offline signature verification system

• Main Authors: Al-Omari, Y. M., Abdullah, S. N. H. S., Omar, K.
• Format: Conference Proceeding
• Language: English
• Subjects: Artificial neural networks; Feature extraction; features extraction; Forgery; Hidden Markov models; Offline signature; Pixel; Support vector machines; verification system
• DOI: 10.1109/ICPAIR.2011.5976912

Biometrics can be classified into two types Behavioral (signature verification, keystroke dynamics, etc.) and Physiological (iris characteristics, fingerprint, etc.). Handwritten signature is 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. 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 the State-of-the-Art about offline signature verification system; this biometric 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. In this paper, we present signature forgery types, features types and recent methods used for features extraction in signature verification systems and approaches used for verification in signature systems. Then we discuss these approaches and for which type of forgeries its suitable. Finally, we suggest new interesting ideas to be incorporated in the future.