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1 Title of the Article Image Processing for Signature Verification
2 Author's name Pallavi V. Hatkar: Department of E& TC Engineering, Sanjay Ghodawat Group of institutions, Atigre, India
3 Author's name Zareen J Tamboli
4 Subject Electronics and Communication Engineering
5 Keyword(s) Artificial Neural Network, Average Error verification rate, Handwritten Signature Verification Probabilistic Neural Network
6 Abstract

As signature is the primary mechanism both for authentication and authorization in legal transactions, the need for efficient auto-mated solutions for signature verification has increased [3]. Unlike a password, PIN, PKI or key cards – identification data that can be forgotten, lost, stolen or shared – the captured values of the handwritten signature are unique to an individual and virtually impossible to duplicate. The primary advantage that signature verification systems have over other type’s technologies is that signatures are already accepted as the common method of identity verification [4]. A signature verification system and the techniques used to solve this problem can be divided into two classes Online and Off-line [5].On-line approach uses an electronic tablet and a stylus connected to a computer to extract information about a signature and takes dynamic information like pressure, velocity, speed of writing etc. for verification purpose. Whereas Off- line signature verification involves less electronic control and uses signature images captured by scanner or camera. An offline signature verification system uses features extracted from scanned signature image. In this only the pixel image needs to be evaluated.

7 Publisher Innovative Research Publication
8 Journal Name; vol., no. International Journal of Innovative Research in Computer Science & Technology (IJIRCST); Volume-3 Issue-3
9 Publication Date May 2015
10 Type Peer-reviewed Article
11 Format PDF
12 Uniform Resource Identifier https://ijircst.org/view_abstract.php?title=Image-Processing-for-Signature-Verification&year=2015&vol=3&primary=QVJULTIxMw==
13 Digital Object Identifier(DOI)  
14 Language English
15 Page No 127-129

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