Palm Print Authentication Using Neural Networks


Himanshu; Parul Kansal

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HCTL Open International Journal of Technology Innovations and Research (IJTIR), e-ISSN: 2321-1814

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Volume 13, January 2015, ISBN:978-1-62951-872-5.

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© 2015 by the Authors; Licensed by HCTL Open, India.

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This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License.


Biometric can be a technology for verification or identification of folks by utilizing a person’s physiological and behavioural traits. Several palm print representations happen to be proposed web hosting authentication, there may be little agreement which palm print representation can offer best representation for reliable authentication. In this particular paper, characterization of user’s identity through the simultaneous usage of two major palm print representations is completed. This paper also investigates comparative performance between Gabor and SVD (Singular Value Decomposition) based palm print representations. A palm print recognition approach using neural net is proposed. Neural networks present you with a number of advantages, including requiring less formal statistical training, capability to implicitly detect complex nonlinear relationships between dependent and independent variables.


SVD (Singular Value Decomposition), Gabor filter, Palm print, Recognition.

Cite this Article

Himanshu; Parul Kansal, Palm Print Authentication Using Neural Networks, HCTL Open International Journal of Technology Innovations and Research (IJTIR), Volume 13, January 2015, e-ISSN: 2321-1814, ISBN: 978-1-62951-872-5.

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