Static Signature Verification and Recognition Through Artificial Neural Network

Authors(4) :-Prof. M. S. Khatib, Prof. Saima Ansari, Aliya Pathan, Eileen Kerketta

For person identification, signature has always been a discriminating feature. Currently, due to advancement there is an increase of authorization via signatures for transaction, especially in the field of finance and business. Therefore, automatic signature verification and recognition should be developed if authenticity is verified and guaranteed successfully on regular terms. Nowadays, huge number of documents, for example: bank cheques, have to be authenticated in limited time but often the signature is unrealistic of the account’s holder in terms of manual verification. Authentication and authorization are the secure means that are provided by signatures. Hence, there is the need of identification systems and automatic signature verification. At the present time, people prefer drawing a shape as their signature instead of hand written signatures, as these are different from other textual type, since it does not have text in it. So, an unusual approach should be kept in account to process such signatures. The present research work is on Static signature recognition system signature verification and recognition have been signature recognition system.

Authors and Affiliations

Prof. M. S. Khatib
Department of Computer Sci. & Engg. Rashtrasant Tukdoji Maharaj Nagpur University, Nagpur, Maharashtra, India
Prof. Saima Ansari
Department of Computer Science and Engineering,Anjuman College of Engineering and Technology, Rashtrasant Tukdoji Maharaj Nagpur University, Nagpur, Maharashtra, India
Aliya Pathan
Department of Computer Sci. & Engg. Rashtrasant Tukdoji Maharaj Nagpur University, Nagpur, Maharashtra, India
Eileen Kerketta
Department of Computer Science and Engineering,Anjuman College of Engineering and Technology, Rashtrasant Tukdoji Maharaj Nagpur University, Nagpur, Maharashtra, India

Authorization, Transaction, Authentication, Automatic, Extraction.

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Publication Details

Published in : Volume 4 | Issue 3 | January-February 2018
Date of Publication : 2018-01-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 331-334
Manuscript Number : NCAEAS4369
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Prof. M. S. Khatib, Prof. Saima Ansari, Aliya Pathan, Eileen Kerketta, " Static Signature Verification and Recognition Through Artificial Neural Network, International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 4, Issue 3, pp.331-334, January-February-2018. Available at doi : 10.32628/NCAEAS4369
Journal URL : http://ijsrst.com/NCAEAS4369

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