Handwritten Signature Verification using Deep Learning
Eman Alajrami, Belal A. M. Ashqar, Bassem S. Abu-Nasser, Ahmed J. Khalil, Musleh M. Musleh, Alaa M. Barhoom & Samy S. Abu-Naser
International Journal of Academic Multidisciplinary Research (IJAMR) 3 (12):39-44 (2020)
Abstract
Every person has his/her own unique signature that is used mainly for the purposes of personal
identification and verification of important documents or legal transactions. There are two kinds of signature
verification: static and dynamic. Static(off-line) verification is the process of verifying an electronic or document
signature after it has been made, while dynamic(on-line) verification takes place as a person creates his/her
signature on a digital tablet or a similar device. Offline signature verification is not efficient and slow for a large
number of documents. To overcome the drawbacks of offline signature verification, we have seen a growth in
online biometric personal verification such as fingerprints, eye scan etc. In this paper we created CNN model
using python for offline signature and after training and validating, the accuracy of testing was 99.70%.
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501 ( #686 of 71,327 )
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