JIT_V1_N4_RP2 Jyoti Singh Manisha Sharma Journal on Information Technology 2277-5250 1 4 35 44 Authentication, Forgeries, FAR (False Acceptance Rate), FRR (False Rejection Rate), Offline Signature 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). September - November 2012 Copyright © 2012 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=2015