Curvelet transform based palm print recognition for biometric authentication.

  • Boobalakumaran S M Bannari Amman Institute of Technology
  • Arunkumar M Bannari Amman Institute of Technology
  • Ramesh S M Bannari Amman Institute of Technology
  • Pradeep Raja R Bannari Amman Institute of Technology
DOI: https://doi.org/10.53555/eee.v1i4.382
Keywords: Curvelet Transform (CT),, Radial Basis Function (RBF),, Primitive Component Analysis (PCA),, Recognition Rate(RR),, ,Compression Rate(CR).

Abstract

An efficient Palm print recognition technique is being proposed here, the system uses the Curvelet Transform (CT) for the process of feature extraction. The CT differs from Discrete Wavelet Transform in a way that the levels used for feature extraction is made to vary. With the help of PCA and RBF neural network we can recognize the authentication by using Curvelet transform to increase the accuracy. Curvelet transform mainly used for predicting several principal lines especially most sparse lines on palm prints. This paper utilizes the Curvelet transform to extract the feature information of palm print images on different scales, deals with the information by dimension reduction of PCA(Principal Component Analysis), then provides the information for RBF network to study and make decisions. Here we are going to increase the speed of computational process to reduce the response time.

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Author Biographies

Boobalakumaran S M, Bannari Amman Institute of Technology

PG Scholar

Arunkumar M, Bannari Amman Institute of Technology

Assistant Professor

Ramesh S M, Bannari Amman Institute of Technology

Associate Professor

Pradeep Raja R, Bannari Amman Institute of Technology

PG Scholar

Published
2015-04-30
How to Cite
S M, B., M, A., S M, R., & Raja R, P. (2015). Curvelet transform based palm print recognition for biometric authentication. IJRDO - Journal of Electrical And Electronics Engineering, 1(4). https://doi.org/10.53555/eee.v1i4.382
Issue
Vol. 1 No. 4 (2015): IJRDO - Journal of Electrical And Electronics Engineering
Section
Articles

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