DocumentCode :
1578855
Title :
An evaluation on offline signature verification using artificial neural network approach
Author :
O-Khalifa, Othman ; Alam, M.K. ; Abdalla, A.H.
Author_Institution :
Dept. of Electr. & Comput. Eng., Int. Islamic Univ. Malaysia, Kuala Lumpur, Malaysia
fYear :
2013
Firstpage :
368
Lastpage :
371
Abstract :
The signature verification is the oldest security technique to verify the identification of persons. Recently, the signature recognition schemes are growing in the world of security technology. It offers two different types of schemes those are offline and online method. The offline technique means to verify a signature written on paper which is scanned to convert it into a digital image, whereas the online system required an online device such as Tablet PC, touch screen monitor by a pressure sensitive pen to verify the signature. This paper discusses a review of offline signature verification schemes which considered as a highly secured technique to recognize the genuine person´s identity. It addresses the offline signature verification technique using Artificial Neural Network (ANN) approach. It also explains the fundamental characteristics of offline signature verification processes and highlights the comparison among various offline signature verification approaches and various signature recognition issues.
Keywords :
handwriting recognition; neural nets; ANN approach; artificial neural network approach; offline signature verification; security technique; signature recognition schemes; Artificial neural networks; Databases; Digital images; Feature extraction; Forgery; Artificial Neural Network; Features extraction and Forgeries; Offline Signature Verification; Preprocessing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Electrical and Electronics Engineering (ICCEEE), 2013 International Conference on
Conference_Location :
Khartoum
Print_ISBN :
978-1-4673-6231-3
Type :
conf
DOI :
10.1109/ICCEEE.2013.6633964
Filename :
6633964
Link To Document :
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