DocumentCode :
2653685
Title :
State-of-the-art in offline signature verification system
Author :
Al-Omari, Yazan M. ; Abdullah, Siti Norul Huda Sheikh ; Omar, Khairuddin
Author_Institution :
Fac. of Inf. Sci. & Technol., Univ. Kebangsaan Malaysia, Kuala Lumpur, Malaysia
Volume :
1
fYear :
2011
fDate :
28-29 June 2011
Firstpage :
59
Lastpage :
64
Abstract :
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.
Keywords :
feature extraction; fingerprint identification; handwriting recognition; handwritten character recognition; iris recognition; behavioral biometrics; biometric identification method; feature extraction; fingerprint; forgeries; handwritten signature; iris characteristics; keystroke dynamics; offline signature verification system; online verification system; physiological biometrics; Artificial neural networks; Feature extraction; Forgery; Hidden Markov models; Pixel; Support vector machines; Offline signature; features extraction; verification system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Analysis and Intelligent Robotics (ICPAIR), 2011 International Conference on
Conference_Location :
Putrajaya
Print_ISBN :
978-1-61284-407-7
Type :
conf
DOI :
10.1109/ICPAIR.2011.5976912
Filename :
5976912
Link To Document :
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