Offline Signature Verification Using Neural Networks

Jyoti Singh*, Manisha Sharma**
*-** Electronics & Telecommunication Department, Bhilai Institute of Technology, Durg (C.G.), India.
Periodicity:September - November'2012
DOI : https://doi.org/10.26634/jit.1.4.2015

Abstract

Signature has been a distinguishing biometric feature through ages. Signature verification finds application in a large number of fields starting from online banking, passport verification systems, online exams etc. Human signatures can be handled as an image and recognized using computer vision and neural network techniques. This paper, proposes an off-line signature verification system using neural network. The system consists of three stages: the first is preprocessing stage, second is feature extraction stage and the last is verification stage using neural network. The objective of the work is to reduce two critical parameters, False Acceptance Rate (FAR) and False Rejection Rate (FRR).

Keywords

Authentication, Forgeries, FAR (False Acceptance Rate), FRR (False Rejection Rate), Offline signature

How to Cite this Article?

Singh, J., and Sharma, M. (2012). Offline Signature Verification Using Neural Networks. i-manager’s Journal on Information Technology, 1(4), 35-44. https://doi.org/10.26634/jit.1.4.2015

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