research-article

Half-orientation extraction of palmprint features

Authors:

David ZhangAuthors Info & Claims

Pattern Recognition Letters, Volume 69, Issue C

Pages 35 - 41

Published: 01 January 2016 Publication History

Abstract

The points in palmprint images usually have two different dominant orientations.Half-orientations can precisely represent the orientation feature of the palmprint.Defining a bank of "half-Gabor" filters for the half-orientation extraction.Our method improves the performance of palmprint recognition. Orientation features of the palmprint are usually used in palmprint recognition methods. Conventional orientation based methods are always based on an assumption that the line in a palmprint is straight and possesses only a single dominant orientation. However, a large number of "lines" in a palmprint are curves. The point in these curves usually has two dominant orientations. Moreover, it can be seen that there are numerous cross wrinkles in a palmprint. The cross point of any two cross wrinkles obviously has two different dominant orientations. In this paper, we proposed a simple and effective double half-orientation based method for feature extraction and recognition of the palmprint. In the method, a bank of "half-Gabor" filters are defined for the half-orientation extraction of a palmprint. Compared with the single dominant orientation, the double half-orientations can more precisely characterize the global orientation feature of a palmprint. Extensive experiments are carried out on three different kinds of palmprint databases and the results show that the proposed method achieves a promising performance in both palmprint verification and identification and outperforms other orientation feature based methods.

References

[1]

A.K. Jain, R. Bolle, S. Pankanti, Biometrics: Personal Identification in Networked Society, Kluwer Academic Publishers, Dordrecht, 1999.

Digital Library

[2]

D. Zhang, Advanced Pattern Recognition Technologies with Applications to Biometrics, Medical Information Science Reference, 2009.

[3]

A.K. Jain, A. Ross, S. Prabhakar, An introduction to biometric recognition., Proc. IEEE Trans. Circuits Syst. Video Technol., 14 (2004) 4-20.

Digital Library

[4]

A. Kong, D. Zhang, M. Kamel, A survey of palmprint recognition, Pattern Recognit., 42 (2009) 1408-1418.

Digital Library

[5]

A.K Jain, J. Feng, Latent palmprint matching, Proc. IEEE Trans. Pattern Anal. Mach. Intell., 30 (2009) 1032-1047.

Digital Library

[6]

D. Zhang, W. Zuo, F. Yue, A comparative study of palmprint recognition algorithms, ACM Comput. Surv., 44 (2012) 2-38.

Digital Library

[7]

J. Malik, D. Girdhar, R. Dahiya, Accuracy improvement in palmprint authentication system, I. J. Image Graph. Signal Process., 4 (2015) 51-59.

[8]

F. Yue, B. Li, M. Yu, Hashing based fast palmprint identification for large-scale databases., Proc. IEEE Trans. Inform. Forensics Secur., 8 (2013) 769-778.

Digital Library

[9]

A. Kumar, S. Shekhar, Personal identification using multibiometrics rank-level fusion, Proc. IEEE Trans. Syst. Man Cybernet. Part C, 41 (2011) 743-752.

Digital Library

[10]

D.S. Huang, W. Jia, D. Zhang, Palmprint verification based on principal lines, Pattern Recognit., 41 (2008) 1316-1328.

Digital Library

[11]

X. Wu, D. Zhang, K. Wang, Palm line extraction and matching for personal authentication, Proc. IEEE Trans. Syst. Man Cybernet. Part A, 36 (2006) 978-987.

Digital Library

[12]

R. Cappelli, M. Ferrara, D. Maico, A fast and accurate palmprint recognition system based on minutiae, Proc. IEEE Trans. Syst. Man Cybernet. Part B, 42 (2012) 956-962.

Digital Library

[13]

E. Liu, A.K. Jain, J. Tian, A coarse to fine minutiae-based latent palmprint matching, Proc. IEEE Trans. Pattern Anal. Mach. Intell., 35 (2013) 2307-2322.

Digital Library

[14]

F. Chen, X. Huang, J. Zhou, Hierarchical minutiae matching for fingerprint and palmprint identification, Proc. IEEE Trans. Image Process., 22 (2013) 4964-4971.

Digital Library

[15]

J. Dai, J. Zhou, Multifeature-based high-resolution palmprint recognition, Proc. IEEE Trans. Pattern Anal. Mach. Intell., 33 (2011) 945-957.

Digital Library

[16]

Y. Xu, L. Fei, D. Zhang, Combing left and right palmprint image for more accurate personal identification, Proc. IEEE Trans. Image Process., 24 (2015) 549-559.

[17]

D. Zhang, W.K. Kong, J. You, L.M. Wong, Online palmprint identification, Proc. IEEE Trans. Pattern Anal. Mach. Intell., 25 (2003) 1041-1050.

Digital Library

[18]

A.W.K. Kong, D. Zhang, Competitive coding scheme for palmprint verification, in: Proceedings of the Seventeenth International Conference on Pattern Recognition (ICPR), 2004, pp. 520-523.

[19]

W. Jia, D. Huang, D. Zhang, Palmprint verification based on robust line orientation code, Pattern Recognit., 41 (2008) 1504-1513.

Digital Library

[20]

A. Kong, D. Zhang, M. Kamel, Palmprint identification using feature-level fusion, Pattern Recognit., 39 (2006) 478-487.

Digital Library

[21]

W. Zuo, Z. Lin, Z. Guo, D. Zhang, The multiscale competitive code via sparse representation for palmprint verification, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010, pp. 2265-2272.

[22]

Z. Sun, T. Tan, Y. Wang, Oridnal palmprint representation for personal identification, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2005, pp. 279-284.

[23]

Z. Guo, D. Zhang, L. Zhang, W. Zuo, Palmprint verification using binary orientation co-occurrence vector, Pattern Recognit. Lett., 30 (2009) 1219-1227.

Digital Library

[24]

L. Zhang, H. Li, J. Niu, Fragile bits in palmprint recognition, Proc. IEEE Signal Process. Lett., 19 (2012) 663-666.

[25]

F. Xue, W. Zuo, K. Wang, A performance evaluation of filter design and coding schemes for palmprint recognition, in: Proceedings of the Nineteenth International Conference on Pattern Recognition (ICPR), 2008, pp. 1-4.

[26]

Ajay Kumar, Incorporating cohort information for reliable palmprint authentication, Bhubaneswar, India, 2008.

Digital Library

[27]

W. Jang, D. Park, D. Lee, S. Kim, Fingerprint image enhancement based on a half Gabor filter, in: Proceedings of the Advances in Biometrics, Springer Berlin Heidelberg, 2005, pp. 258-264.

[28]

D. Zhang, Z. Guo, G. Lu, L. Zhang, W. Zuo, An online system of multi-spectral palmprint verification, Proc. IEEE Trans. Instrum. Meas., 59 (2010) 480-490.

Cited By

Pranjal SKong A(2019)Palmprint Recognition Using Realistic Animation Aided Data Augmentation2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems (BTAS)10.1109/BTAS46853.2019.9186003(1-9)Online publication date: 23-Sep-2019
https://dl.acm.org/doi/10.1109/BTAS46853.2019.9186003
Maadeed SJiang XRida IBouridane A(2019)Palmprint identification using sparse and dense hybrid representationMultimedia Tools and Applications10.1007/s11042-018-5655-878:5(5665-5679)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1007/s11042-018-5655-8
Attallah BSerir AChahir Y(2019)Feature extraction in palmprint recognition using spiral of moment skewness and kurtosis algorithmPattern Analysis & Applications10.1007/s10044-018-0712-522:3(1197-1205)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s10044-018-0712-5
Show More Cited By

Half-orientation extraction of palmprint features
1. Computing methodologies
  1. Computer graphics
  2. Machine learning
    1. Machine learning algorithms

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Published In

cover image Pattern Recognition Letters

Pattern Recognition Letters Volume 69, Issue C

January 2016

96 pages

ISSN:0167-8655

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Copyright © Elsevier B.V.

Publisher

Elsevier Science Inc.

United States

Publication History

Published: 01 January 2016

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Cited By

Pranjal SKong A(2019)Palmprint Recognition Using Realistic Animation Aided Data Augmentation2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems (BTAS)10.1109/BTAS46853.2019.9186003(1-9)Online publication date: 23-Sep-2019
https://dl.acm.org/doi/10.1109/BTAS46853.2019.9186003
Maadeed SJiang XRida IBouridane A(2019)Palmprint identification using sparse and dense hybrid representationMultimedia Tools and Applications10.1007/s11042-018-5655-878:5(5665-5679)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1007/s11042-018-5655-8
Attallah BSerir AChahir Y(2019)Feature extraction in palmprint recognition using spiral of moment skewness and kurtosis algorithmPattern Analysis & Applications10.1007/s10044-018-0712-522:3(1197-1205)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s10044-018-0712-5
Gumaei ASammouda RAl-Salman AAlsanad A(2018)An Improved Multispectral Palmprint Recognition System Using Autoencoder with Regularized Extreme Learning MachineComputational Intelligence and Neuroscience10.1155/2018/80416092018Online publication date: 27-May-2018
https://dl.acm.org/doi/10.1155/2018/8041609
Li HQiu JYu C(2018)Palmprint Template Protection Scheme with Matrix TransformationProceedings of the 1st International Conference on Control and Computer Vision10.1145/3232651.3232662(3-7)Online publication date: 15-Jun-2018
https://dl.acm.org/doi/10.1145/3232651.3232662
Zhao WPang LXiao KWang HCao ZZhao H(2018)Palmprint recognition using a modified competitive code with distinctive extended neighbourhoodIET Computer Vision10.1049/iet-cvi.2018.530612:8(1151-1162)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1049/iet-cvi.2018.5306
Tabejamaat MMousavi A(2018)Generalized Gabor filters for palmprint recognitionPattern Analysis & Applications10.1007/s10044-017-0638-321:1(261-275)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1007/s10044-017-0638-3
Jia WZhang BLu JZhu YZhao YZuo WLing H(2017)Palmprint Recognition Based on Complete Direction RepresentationIEEE Transactions on Image Processing10.1109/TIP.2017.270542426:9(4483-4498)Online publication date: 11-Jul-2017
https://dl.acm.org/doi/10.1109/TIP.2017.2705424
Bai XGao NZhang ZZhang D(2017)3D palmprint identification combining blocked ST and PCAPattern Recognition Letters10.1016/j.patrec.2017.10.008100:C(89-95)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1016/j.patrec.2017.10.008
Tabejamaat MMousavi A(2017)Concavity-orientation coding for palmprint recognitionMultimedia Tools and Applications10.1007/s11042-016-3544-676:7(9387-9403)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1007/s11042-016-3544-6
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