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International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.5, No.7, Jun. 2013

A Robust Palmprint Recognition System Based on Both Principal Lines and Gabor Wavelets

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Author(s)

Nouha BEN MAHFOUDH,Yousra BEN JEMAA,Faouzi BOUCHHIMA

Index Terms

Person recognition, Palmprint, Principal lines, geometrical feature, Gabor wavelets

Abstract

We present in this paper a new palmprint recognition system based on the principal lines of the palm. An original algorithm is proposed in order to detect automatically principal lines and extract their corre-spondent geometrical features. Given the complexity of the palmprint recognition and in order to ameliorate performances, we propose a hybrid approach based on both geometrical and gabor features.
A comparative study between the three feature vectors obtained from the geometrical approach, global approach and combination of both has proved that the geometrical features are the most relevant since they can give the best compromise recognition Rate/Time. Moreover, a combination of geometrical features with global features can improve recognition rate while keeping the same recognition and learning times. Obtained results also show that the hybrid approach performances are very satisfactory and even surpass the very popular ones.

Cite This Paper

Nouha BEN MAHFOUDH,Yousra BEN JEMAA,Faouzi BOUCHHIMA,"A Robust Palmprint Recognition System Based on Both Principal Lines and Gabor Wavelets", IJIGSP, vol.5, no.7, pp.1-8, 2013.DOI: 10.5815/ijigsp.2013.07.01

Reference

[1]Gorodnichy, D.O., "Multi-order biometric score analysis framework and its application to designing and evaluat-ing biometric systems for access and border control", IEEE Workshop on Computational Intelligence in Bio-metrics and Identity Management (CIBIM), pp 44 – 53 (2011)

[2]Monwar, M.M, "A novel fuzzy multimodal infor-mationfusion technology for human biometric traits identifica-tion", International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC ), pp 112 - 119, Au-gust (2011)

[3]Y. Ben Jemaa, A. Derbel and A. B. Jmâa, "2DPCA frac-tal features and genetic algorithm for efficient face representation and recognition", Eurasip jour-nal on Information Security, Vol. 2011, N. 1(2011) 

[4]D. S. Huang, W. Jia, and D. Zhang, "Palmprint veri-fica-tion based on principal lines", Pattern Recogni-tion, Vol.41, pp. 1316-1328, April (2008) 

[5]A. Kongo, D. Zhang and M. Kamel, "A survey of palmprint recognition", Pattern Recognition, Vol.42, pp. 1408-1418 (2009)

[6]C.Han, H.Cheng, C.Lin and K.C. Fan, "Personal authen-tication using palmprint features", Pattern Recognition, Vol.36, N.2, pp. 371–381 (2003)

[7]Rotinwa-Akinbile, M.O.Aibinu and A.M. Salami, "Palmprint Recognition Using Principal Lines Char-acteri-zation", International Conference on Informatics and Computational Intelligence (ICI), pp. 278-282, December (2011)

[8]L.Zhang and D.Zhang, "Characterization of Palm-prints by Wavelet Signatures via Directional Context Model-ing", IEEE Trans. on SMC— B, Vol.34, N.3, pp. 1335-1347, June (2004)

[9]Yan-Xia Wang and Guang-Hua Sun, "Palmprint recog-nition using Palm-line direction field texture feature", International Conference on Machine Learning and Cybernetics (ICMLC), Vol. 3, pp. 1130-1134, July (2012)

[10]D. Zhang, A. Kong, J. You and M. Wong, "Online palmprint identification", IEEE Trans. Pattern. Anal. Mach. Intell. Vol.25, N.9, pp. 1041–1050 (2004)

[11]A. Kong, D. Zhang and M. Kamel, "Palmprint iden-tific-ation using feature-level fusion", Pattern Recognition, Vol. 39, pp. 478–487 (2006)

[12]X. Pan, and Q.-Q. Ruan, "Palmprint recognition using Gabor feature-based (2D)2PCA", Neurocom-puting, Vol. 71, pp. 3032–3036 (2008)

[13]Zhong-Qiu, De-Shuang and Wei Jia, "Palmprint recog-nition with 2DPCA+PCA based on modular neural net-works" Neurocomputing, Vol. 71, pp. 448–454 (2007)

[14]Xin Pan and Q.Ruan, "Palmprint recognition with im-proved two-dimensional locality preserving pro-ject-tions", Image Vision Comput. Vol. 26, N.9, pp. 261-1268 (2008)

[15]Qingqing Fu, Aiping Wu and Yonghua Li, "Finger-print Identification System Based on SOPC", Inter-national Conference on Wireless Communications, Networking and Mobile Computing (WiCOM), pp.1 – 4, September (2011)

[16]Y. Ben Jemaa and S. Khanfir, "Automatic local Gabor Features extraction for face recognition", International journal on Computer Science and Information Security, Vol. 3, N. 1, pp. 116-122 (2009)

[17]G. K. Michael, T. Connie and A. B. J. Teoh, "Touch-less palmprint biometrics: Novel design and imple-menta-tion", Image Vision Comput, Vol. 26, N.12, pp. 1551– 1560, December (2008)

[18]Sulaiman, S.N.and Isa, N.A.M., "Adaptive fuzzy-K-means clustering algorithm for image seg-mentation", IEEE Transactions on Consumer Elec-tronics, Vol. 56, N.4, pp. 2661 – 2668, November (2010)

[19]N. Otsu, "A thresholding selection method from gray-level histograms", IEEE Trans. Sys, Man and Cyb, Vol.9, N.1, pp. 62-66

[20]Kanungo, P.Nanda, P.K. and Ghosh, A., "Parallel genetic algorithm based adaptive thresholding for image seg-mentation under uneven lighting condi-tions", Interna-tional Conference on Systems Man and Cybernetics (SMC), pp. 1904-1911, October (2010)

[21]Srijeyanthan K., Thusyanthan A., Joseph C.N., Kokulakumaran S., Gunasekara C. and Gamage C., "Skeletonization in a real-time gesture recognition sys-tem", International Conference on Information and Au-tomation for Sustainability (ICIAFs), pp. 213 - 218, December (2010)

[22]B. Z, S. Sh, X. Ch and W. Gao, " Histogram of Ga-bor Phase Patterns (HGPP): A Novel Object Repre-sentation Approach for Face Recognition'', IEEE Trans. on Image Processing, Vol.16, N.1, pp.57-68 (2007)

[23]PolyU Palmprint Database, http://www4.comp.polyu.edu.hk/~biometrics/