An Evaluation on Offline Signature Verification using Artificial Neural Network Approach

被引:0
|
作者
o-Khalifa, Othman [1 ]
Alam, Md. Khorshed [1 ]
Abdalla, Aisha Hassan [1 ]
机构
[1] Int Islamic Univ, Dept Elect & Comp Engn, Kuala Lumpur, Malaysia
来源
2013 INTERNATIONAL CONFERENCE ON COMPUTING, ELECTRICAL AND ELECTRONICS ENGINEERING (ICCEEE) | 2013年
关键词
Offline Signature Verification; Artificial Neural Network; Preprocessing; Features extraction and Forgeries; RECOGNITION;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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.
引用
收藏
页码:368 / 371
页数:4
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