Palmprint Recognition Using 2-D Wavelet, Ridgelet, Curvelet and Contourlet

Vol. 7 No. 1

Year: 2013

Issue : Jul-Sep

Title : Palmprint Recognition Using 2-D Wavelet, Ridgelet, Curvelet and Contourlet

Author Name : Hatem Elaydi, Mohammed Alhanjouri, Mohanad A. M. Abukmeil

Synopsis :

Palmprint recognition is a promising biometric field which is used for forensic and commercial applications. This paper provides a comparative palmprint recognition approach using multi-scale transforms: 2D wavelets, ridgelets, curvelets, and contourlets for feature extraction phase, 2-D Principal Component Analysis (2-D PCA) for dimensionality reduction and artificial neural network for recognition phase. Finally, a comparative analysis has been done. The algorithms have been tested using PolyU hyperspectral palmprint database. The recognition rate accuracy was very good and is listed in this order curvelets, contourlets, ridgelets, and 2D discrete wavelets where the curvelets outperformed the others.

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