Palmprint recognition is gaining grounds as a biometric system for forensic and commercial applications. Palmprint recognition addressed the recognition issue using low and high resolution images. This paper uses PolyU hyperspectral palmprint database, and applies back-propagation neural network for recognition, linear discriminate analysis for dimensionality reduction, and 2D discrete wavelet, ridgelet, curvelet, and contourlet for feature extraction. The recognition rate accuracy shows that contourlet outperforms other transforms.
| Published in | Science Journal of Circuits, Systems and Signal Processing (Volume 2, Issue 5) |
| DOI | 10.11648/j.cssp.20130205.13 |
| Page(s) | 112-118 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2013. Published by Science Publishing Group |
2D Discrete Wavelet, Ridgelet, Curvelet, Contourlet, Linear Discriminate Analysis, Neural Network
| [1] | D. Zhang, Wai-Kin Kong, J. You and Michael Wong, "Online palmprint identification," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, pp. 1041-1050, Sept. 2003. |
| [2] | A. Jain, R. Bolle and S. Pankanti (eds.), Biometrics: Personal Identification in Networked Society, Boston, Mass: Kluwer Academic Publishers, 1999. |
| [3] | A. Kong, D. Zhang and M. Kamel, "A survey of palmprint recognition," Journal of Pattern Recognition, vol. 42, pp. 1408-1418, July. 2009. |
| [4] | H.B.Kekre, R. Vig and S. Bisani, "Identification of multi-spectral palmprints using energy compaction by hybrid wavelet," International Conference on Biometric (ICB), pp. 433-438, March. 2012. |
| [5] | M. Sharkas, I. El-Rube and M.A. Mostafa, "The contourlet transform with the principal component analysis for palmprint recognition," International Conference on Computational Intelligence, Communication Systems and Networks (CICSyN), pp. 262-267, July. 2010. |
| [6] | H.Masood, M. Asim, M. Mumtaz and A. Mansoor,"Combined contourlet and non-subsampled contourlet transforms based approach for personal identification using palmprint," Digital Image Computing: Techniques and Applications, DICTA '09, pp.408-415, Dec.2009. |
| [7] | J. Andrew Bangham and Richard V. Aldridge, "Multiscale decomposition using median and morphological filters," IEEE Winter Workshop on Nonlinear Digital Signal Processing, 6.1_1.1 - 6.1_1.4, 1993. |
| [8] | Alexandru Isar, Sorin Moga, and Xavier Lurton, "A statistical analysis of the 2d discrete wavelet transform," Proceedings of the International Conference AMSDA 2005, 1275-1281, 17-20 May 2005 |
| [9] | Samuel Foucher, Goz´e Bertin B´eni´e, Jean-Marc Boucher,"Multiscale map filtering of sar images," IEEE Transactions on Image Processing, vol. 10, no.1, January 2001, 49-60. |
| [10] | E. J. Candµes, Ridgelets: Theory and Applications, Ph.D. thesis, Department of Statistics, Stanford University, 1998. |
| [11] | E. J. Candµes and D. L. Donoho, "Ridgelets: a key to higher- dimensional intermittency?" Phil. Trans. R. Soc. Lond. A., pp. 2495-2509, 1999. |
| [12] | G. T. Herman, Image Reconstruction from Projections: The Fundamentals of Computerized Tomography, Academic Press, 1980. |
| [13] | A. Rosenfeld and A. C. Kak, Digital Picture Processing, Aca- demic Press, 2nd edition, 1982.. |
| [14] | H. Führ, L. Demaret and F. Friedrich, Beyond wavelets: new image representation paradigms. Book chapter. In: M. Barni and F. Bartolini (Eds.), Document and Image Compression, CRC Press, Boca Raton, FL, 2006. |
| [15] | E. Candes and D. Donoho. "New tight frames of curvelets and optimal representations of objects with C2 singularities," Commun. Pure Appl. Math. 57, pp. 219–266, 2004. |
| [16] | J. Starck, E. Candes and D. Donoho. "The Curvelet Transform for Image Denoising," IEEE Transactions on Image Processing, 11, pp. 670–684, 2002. |
| [17] | M. Do. Directional multiresolution image representation, Thesis, Swiss Federal Institute of Technology, 2001. |
| [18] | M. Do and M. Vetterli. "The contourlet transform: an efficient directional multiresolution image representation," IEEE Transactions Image on Processing, 14 (12), pp. 2091-2106, Dec. 2005. |
| [19] | R. Bamberger and M. Smith. "A filter bank for the directional decomposition of images: Theory and design," IEEE Trans. Signal Proc. 40, 1992, pp. 882-893. |
| [20] | Th Liwei Wang, Xiao Wang, Xuerong Zhang and Jufu Feng, "The equivalence of two-dimensional PCA to line-based PCA," Pattern Recognition Letters, 26 (1), pp. 57-60, Jan 2005. |
| [21] | J. Yang and D. Zhang,"Two-dimensional PCA: A new approach to appearance-based face representation and recognition," IEEE Trans. Pattern Anal. Machine Intell. PAMI-26 (1), 131-137, 2004 |
| [22] | W.S. Zheng, J.H. Lai, S.Z. Li, "1D-LDA vs. 2DLDA: When is vector-based linear discriminate analysis better than matrix-based?" Pattern Recognition, vol. 41, pp. 2156-2172, July 2008. |
| [23] | P.Latha, L.Ganesan and S.Annadurai, "Face recognition using neural networks," Signal Processing: An International Journal (SPIJ) 3 (5), 153-160, Nov 2009. |
| [24] | S.Lawrence, C.L.Giles, A.C.Tsoi, and A.d.Back, "Face recognition: a convolutional neural network approach," IEEE Transactions of Neural Networks, vol.8, no.1, pp.98-113, 1993. |
| [25] | Department of Computing, The Hong Kong Polytechnic University (PolyU), Hyperspectra Palmprint database, Polyu, accessed on Aug. 22, 2013, available at: http://www4.comp.polyu.edu.hk/~biometrics/Hyperspectral Palmprint/HSP.htm. |
| [26] | Zhenhua Guo, Lei Zhang, and David Zhang, "feature band selection for multispectral palmprint recognition," International Conference on Pattern Recognition, pp. 1136-1139, 2010. |
| [27] | The Curvelet.org. Accessed: September, 2013. Available at: http://www.curvelet.org/ |
| [28] | H. Elaydi, M. Alhanjouri, and M. Abukmeil, "Palmprint recognition using 2-d wavelet, ridgelet, curvelet and contourlet," to appear in i-manager's Journal on Electrical Engineering (JEE), 2013. |
APA Style
Hatem Elaydi, Mohanad A. M. Abukmeil, Mohammed Alhanjouri. (2013). Palmprint Recognition Using Multiscale Transform, Linear Discriminate Analysis, and Neural Network. Science Journal of Circuits, Systems and Signal Processing, 2(5), 112-118. https://doi.org/10.11648/j.cssp.20130205.13
ACS Style
Hatem Elaydi; Mohanad A. M. Abukmeil; Mohammed Alhanjouri. Palmprint Recognition Using Multiscale Transform, Linear Discriminate Analysis, and Neural Network. Sci. J. Circuits Syst. Signal Process. 2013, 2(5), 112-118. doi: 10.11648/j.cssp.20130205.13
AMA Style
Hatem Elaydi, Mohanad A. M. Abukmeil, Mohammed Alhanjouri. Palmprint Recognition Using Multiscale Transform, Linear Discriminate Analysis, and Neural Network. Sci J Circuits Syst Signal Process. 2013;2(5):112-118. doi: 10.11648/j.cssp.20130205.13
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.cssp.20130205.13,
author = {Hatem Elaydi and Mohanad A. M. Abukmeil and Mohammed Alhanjouri},
title = {Palmprint Recognition Using Multiscale Transform, Linear Discriminate Analysis, and Neural Network},
journal = {Science Journal of Circuits, Systems and Signal Processing},
volume = {2},
number = {5},
pages = {112-118},
doi = {10.11648/j.cssp.20130205.13},
url = {https://doi.org/10.11648/j.cssp.20130205.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cssp.20130205.13},
abstract = {Palmprint recognition is gaining grounds as a biometric system for forensic and commercial applications. Palmprint recognition addressed the recognition issue using low and high resolution images. This paper uses PolyU hyperspectral palmprint database, and applies back-propagation neural network for recognition, linear discriminate analysis for dimensionality reduction, and 2D discrete wavelet, ridgelet, curvelet, and contourlet for feature extraction. The recognition rate accuracy shows that contourlet outperforms other transforms.},
year = {2013}
}
TY - JOUR T1 - Palmprint Recognition Using Multiscale Transform, Linear Discriminate Analysis, and Neural Network AU - Hatem Elaydi AU - Mohanad A. M. Abukmeil AU - Mohammed Alhanjouri Y1 - 2013/11/10 PY - 2013 N1 - https://doi.org/10.11648/j.cssp.20130205.13 DO - 10.11648/j.cssp.20130205.13 T2 - Science Journal of Circuits, Systems and Signal Processing JF - Science Journal of Circuits, Systems and Signal Processing JO - Science Journal of Circuits, Systems and Signal Processing SP - 112 EP - 118 PB - Science Publishing Group SN - 2326-9073 UR - https://doi.org/10.11648/j.cssp.20130205.13 AB - Palmprint recognition is gaining grounds as a biometric system for forensic and commercial applications. Palmprint recognition addressed the recognition issue using low and high resolution images. This paper uses PolyU hyperspectral palmprint database, and applies back-propagation neural network for recognition, linear discriminate analysis for dimensionality reduction, and 2D discrete wavelet, ridgelet, curvelet, and contourlet for feature extraction. The recognition rate accuracy shows that contourlet outperforms other transforms. VL - 2 IS - 5 ER -
Email: