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Volume 8 Issue 5
May  2021

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2021  >  8(5): 1038-1051
X. Chen, M. Yu, F. Yue, and B. Li, "Orientation Field Code Hashing: A Novel Method for Fast Palmprint Identification," IEEE/CAA J. Autom. Sinica, vol. 8, no. 5, pp. 1038-1051, May. 2021. doi: 10.1109/JAS.2020.1003186
Citation: X. Chen, M. Yu, F. Yue, and B. Li, "Orientation Field Code Hashing: A Novel Method for Fast Palmprint Identification," IEEE/CAA J. Autom. Sinica, vol. 8, no. 5, pp. 1038-1051, May. 2021. doi: 10.1109/JAS.2020.1003186
shu

Orientation Field Code Hashing: A Novel Method for Fast Palmprint Identification

doi: 10.1109/JAS.2020.1003186
  • 1.

    School of Electronic and Information Engineering, Hebei University of Technology (HEBUT), Tianjin 300401, China

  • 2.

    Beijing Institute of New Technology Applications, Beijing Academy of Sciences and Technology, Beijing 100035, China

  • 3.

    School of Artificial Intelligence, Hebei University of Technology (HEBUT), Tianjin 300130, China

Funds:  This work was supported in part by the National Natural Science Foundation of China (61806071), the Natural Science Foundation of Hebei Province (F2019202464, F2019202381), the Open Project Program of the National Laboratory of Pattern Recognition (NLPR) of China (201900043), Hebei Provincial Education Department Youth Foundation (QN2019207), and the Technical Expert Project of Tianjin (19JCTPJC55800, 19JCTPJC57000)
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    Abstract
  • For a large-scale palmprint identification system, it is necessary to speed up the identification process to reduce the response time and also to have a high rate of identification accuracy. In this paper, we propose a novel hashing-based technique called orientation field code hashing for fast palmprint identification. By investigating hashing-based algorithms, we first propose a double-orientation encoding method to eliminate the instability of orientation codes and make the orientation codes more reasonable. Secondly, we propose a window-based feature measurement for rapid searching of the target. We explore the influence of parameters related to hashing-based palmprint identification. We have carried out a number of experiments on the Hong Kong PolyU large-scale database and the CASIA palmprint database plus a synthetic database. The results show that on the Hong Kong PolyU large-scale database, the proposed method is about 1.5 times faster than the state-of-the-art ones, while achieves the comparable identification accuracy. On the CASIA database plus the synthetic database, the proposed method also achieves a better performance on identification speed.

     

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  • [1]
    X. Y. Jing and D. Zhang, “A face and palmprint recognition approach based on discriminant DCT feature extraction,” IEEE Trans. Syst. Man Cybern. B Cybern., vol. 34, no. 6, pp. 2405–2415, Dec. 2004. doi: 10.1109/TSMCB.2004.837586
    [2]
    D. Zhang, W. K. Kong, J. You, and M. Wong, “Online palmprint identification,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 9, pp. 1041–1050, Sep. 2003. doi: 10.1109/TPAMI.2003.1227981
    [3]
    L. K. Fei, G. M. Lu, J. Wei, S. H. Teng, and D. Zhang, “Feature extraction methods for palmprint recognition: A survey and evaluation,” IEEE Trans. Syst. Man Cybern.:Syst., vol. 49, no. 2, pp. 346–363, Feb. 2019. doi: 10.1109/TSMC.2018.2795609
    [4]
    C. H. Zhang, W. F. Zhong, C. Y. Zhan, and X. Qin, “Double half-orientation code and nonlinear matching scheme for palmprint recognition,” in Proc. Int. Conf. Mechatronics and Intelligent Robotics, Kunming, China, 2018, pp. 36–42.
    [5]
    W. Jia, R. X. Hu, Y. K. Lei, Y. Zhao, and J. Gui, “Histogram of oriented lines for palmprint recognition,” IEEE Trans. Syst. Man Cybern:Syst, vol. 44, no. 3, pp. 385–395, Mar. 2014. doi: 10.1109/TSMC.2013.2258010
    [6]
    Q. L. Sun, J. X. Zhang, A. Q. Yang, and Q. Zhang, “Palmprint recognition with deep convolutional features,” in Proc. Chinese Conf. Image and Graphics Technologies, Beijing, China, 2017, pp. 12–19.
    [7]
    S. P. Zhao, B. Zhang, and C. L. P. Chen, “Joint deep convolutional feature representation for hyperspectral palmprint recognition,” Inform. Sci., vol. 489, pp. 167–181, Jul. 2019. doi: 10.1016/j.ins.2019.03.027
    [8]
    D. X. Zhong and J. S. Zhu, “Centralized large margin cosine loss for open-set deep palmprint recognition,” IEEE Trans. Circ. Syst. Video Technol., vol. 30, no. 6, pp. 1559–1568, Jun. 2020. doi: 10.1109/TCSVT.2019.2904283
    [9]
    D. Zhang, W. M. Zuo, and F. Yue, “A comparative study of palmprint recognition algorithms,” ACM Comput. Surv., vol. 44, no. 1, Article No. 2, Jan. 2012.
    [10]
    M. Baveja, H. S. Yuan, and L. M. Wein, “Asymptotic biometric analysis for large gallery sizes,” IEEE Trans. Inform. Foren. Sec., vol. 5, no. 4, pp. 955–964, Dec. 2010. doi: 10.1109/TIFS.2010.2058105
    [11]
    A. Gyaourova and A. Ross, “Index codes for multibiometric pattern retrieval,” IEEE Trans. Inform. Foren. Sec., vol. 7, no. 2, pp. 518–529, Apr. 2012. doi: 10.1109/TIFS.2011.2172429
    [12]
    F. Yue, B. Li, M. Yu, and J. Q. Wang, “Hashing based fast palmprint identification for large-scale databases,” IEEE Trans. Inform. Foren. Sec., vol. 8, no. 5, pp. 769–778, May 2013. doi: 10.1109/TIFS.2013.2253321
    [13]
    F. Yue, H. L. Ding, B. Li, and X. Chen, “Accelerated POP hashing for fast palmprint identification on large-scale databases,” in Proc. 36th Chinese Control Conf. (CCC), Dalian, China, 2017, pp. 11121–11126.
    [14]
    J. You, W. X. Li, and D. Zhang, “Hierarchical palmprint identification via multiple feature extraction,” Pattern Recogn., vol. 35, no. 4, pp. 847–859, Apr. 2002. doi: 10.1016/S0031-3203(01)00100-5
    [15]
    W. X. Li, J. You, and D. Zhang, “Texture-based palmprint retrieval using a layered search scheme for personal identification,” IEEE Trans. Multim., vol. 7, no. 5, pp. 891–898, Oct. 2005. doi: 10.1109/TMM.2005.854380
    [16]
    Z. H. Xie, Z. H. Guo, and C. S. Qian, “Palmprint gender classification by convolutional neural network,” IET Comput. Vis., vol. 12, no. 4, pp. 476–483, Jun. 2018. doi: 10.1049/iet-cvi.2017.0475
    [17]
    M. V. N. K. Prasad, “A novel technique for palmprint classification and authentication,” Int. J. Biomet., vol. 2, no. 1, pp. 87–108, Jan. 2010. doi: 10.1504/IJBM.2010.030418
    [18]
    S. F. Yue, W. M. Zuo, D. Zhang, and K. Q. Wang, “Competitive code-based fast palmprint identification using a set of cover trees,” Opt. Eng., vol. 48, no. 6, Article No. 067204, Jun. 2009. doi: 10.1117/1.3156846
    [19]
    F. Yue, W. M. Zuo, D. Zhang, and B. Li, “Fast palmprint identification with multiple templates per subject,” Pattern Recogn. Lett., vol. 32, no. 8, pp. 1108–1118, Jun. 2011. doi: 10.1016/j.patrec.2011.02.019
    [20]
    J. Wang, S. Kumar, and S. F. Chang, “Semi-supervised hashing for scalable image retrieval,” in Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition, San Francisco, CA, USA, 2010, pp. 3424–3431.
    [21]
    R. Salakhutdinov and G. Hinton, “Semantic hashing,” Int. J. Approx. Reason., vol. 50, no. 7, pp. 969–978, Jul. 2009. doi: 10.1016/j.ijar.2008.11.006
    [22]
    W. Liu, C. Mu, S. Kumar, and J. F. Chang, “Discrete graph hashing,” in Proc. 27th Int. Conf. Neural Information Processing Systems, Cambridge, MA, USA, 2014, pp. 3419–3427.
    [23]
    F. M. Shen, C. H. Shen, W. Liu, and H. T. Shen, “Supervised discrete hashing,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition, Boston, MA, USA, 2015, pp. 37–45.
    [24]
    J. Wang, W. Liu, S. Kumar, and S. F. Chang, “Learning to hash for indexing big data-A survey,” Proc. IEEE, vol. 104, no. 1, pp. 34–57, Jan. 2016. doi: 10.1109/JPROC.2015.2487976
    [25]
    L. R. Han, P. Li, X. Bai, C. Grecos, X. Y. Zhang, and P. Ren, “Cohesion intensive deep hashing for remote sensing image retrieval,” Remote Sens., vol. 12, no. 1, Article No. 101, Jan. 2020.
    [26]
    Y. N. Li, L. Wan, T. Fu, and W. J. Hu, “Piecewise supervised deep hashing for image retrieval,” Multimed. Tools Appl., vol. 78, no. 17, pp. 24431–24451, Sep. 2019. doi: 10.1007/s11042-018-7072-4
    [27]
    H. Cevikalp, M. Elmas, and S. Ozkan, “Towards category based large-scale image retrieval using transductive support vector machines,” in Proc. European Conf. Computer Vision, Amsterdam, The Netherlands, 2016, pp. 621–637.
    [28]
    J. Wang, S. Kumar, and S. F. Chang, “Semi-supervised hashing for large-scale search,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 12, pp. 2393–2406, Dec. 2012. doi: 10.1109/TPAMI.2012.48
    [29]
    C. C. Chen and S. L. Hsieh, “Using binarization and hashing for efficient SIFT matching,” J. Vis. Commun. Image Represent., vol. 30, pp. 86–93, Jul. 2015. doi: 10.1016/j.jvcir.2015.02.014
    [30]
    J. P. Heo, Y. Lee, J. F. He, S. F. Chang, and S. E. Yoon, “Spherical hashing,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition, Providence, RI, USA, 2012, pp. 2957–2964.
    [31]
    Z. Sun, T. N. Tan, Y. H. Wang, and S. Z. Li, “Ordinal palmprint represention for personal identification,” in Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition, San Diego, CA, USA, 2005, pp. 279–284.
    [32]
    W. Jia, D. S. Huang, and D. Zhang, “Palmprint verification based on robust line orientation code,” Pattern Recogn., vol. 41, no. 5, pp. 1504–1513, May 2008. doi: 10.1016/j.patcog.2007.10.011
    [33]
    C. M. Pun, C. P. Yan, and X. C. Yuan, “Robust image hashing using progressive feature selection for tampering detection,” Multimed. Tools Appl., vol. 77, no. 10, pp. 11609–11633, May 2018. doi: 10.1007/s11042-017-4809-4
    [34]
    D. S. Huang, W. Jia, and D. Zhang, “Palmprint verification based on principal lines,” Pattern Recogn., vol. 41, no. 4, pp. 1316–1328, Apr. 2008. doi: 10.1016/j.patcog.2007.08.016
    [35]
    H. K. Kalluri and M. V. N. K. Prasad, “Palmprint identification using Gabor and wide principal line features,” Procedia Comput. Sci., vol. 93, pp. 706–712, Sep. 2016. doi: 10.1016/j.procs.2016.07.272
    [36]
    F. Hao, J. Daugman, and P. Zielinski, “A fast search algorithm for a large fuzzy database,” IEEE Trans. Inform. Foren. Sec., vol. 3, no. 2, pp. 203–212, Jun. 2008. doi: 10.1109/TIFS.2008.920726
    [37]
    W. X. Bian, S. F. Ding, and Y. Xue, “Combining weighted linear project analysis with orientation diffusion for fingerprint orientation field reconstruction,” Inform. Sci., vol. 396, pp. 55–71, Aug. 2017. doi: 10.1016/j.ins.2017.02.043
    [38]
    L. K. Fei, Y. Xu, W. L. Tang, and D. Zhang, “Double-orientation code and nonlinear matching scheme for palmprint recognition,” Pattern Recogn., vol. 49, pp. 89–101, Jan. 2016. doi: 10.1016/j.patcog.2015.08.001
    [39]
    Polyu Palmprint Database. [Online]. Available: http://www.comp.polyu.edu.hk/biometrics/, Mar. 21, 2020.
    [40]
    Casia Palmprint Database. [Online]. Available: http://biometrics.idealtest.org/dbDetailForUser.do?id=5, Mar.21, 2020.
    [41]
    Z. Khan, A. Mian, and Y. Q. Hu, “Contour code: Robust and efficient multispectral palmprint encoding for human recognition,” in Proc. Int. Conf. Computer Vision, Barcelona, Spain, 2011, pp. 1935–1942.
    [42]
    F. Yue, B. Li, M. Yu, and J. Q. Wang, “Fast palmprint identification using orientation pattern hashing,” in Proc. Int. Conf. Hand-based Biometrics, Hong Kong, China, 2011, pp. 1–6.
    [43]
    G. S. Badrinath, P. Gupta, and H. Mehrotra, “Score level fusion of voting strategy of geometric hashing and SURF for an efficient palmprint-based identification,” J. Real-Time Image Proc., vol. 8, no. 3, pp. 265–284, Sep. 2013. doi: 10.1007/s11554-011-0229-2
    [44]
    A. K. Jain, A. Ross, and S. Prabhakar, “An introduction to biometric recognition,” IEEE Trans. Circ. Syst. Video Technol., vol. 14, no. 1, pp. 4–20, Jan. 2004.
    [45]
    A. Kong, D. Zhang, and K. Mohamed, “Palmprint identification using feature-level fusion,” Pattern Recogn., vol. 39, no. 3, pp. 478–487, Mar. 2006. doi: 10.1016/j.patcog.2005.08.014
    [46]
    I. Rida, R. Herault, G. L. Marcialis, and G. Gasso, “Palmprint recognition with an efficient data driven ensemble classifier,” Pattern Recogn. Lett., vol. 126, pp. 21–30, Sep. 2019. doi: 10.1016/j.patrec.2018.04.033
    [47]
    X. Q. Wu, Q. S. Zhao, and W. Bu, “A SIFT-based contactless palmprint verification approach using iterative RANSAC and local palmprint descriptors,” Pattern Recogn., vol. 47, no. 10, pp. 3314–3326, Oct. 2014. doi: 10.1016/j.patcog.2014.04.008
    [48]
    W. Jia, B. Zhang, J. T. Lu, Y. H. Zhu, Y. Zhao, W. M. Zuo, and H. B. Ling, “Palmprint recognition based on complete direction representation,” IEEE Trans. Image Proc., vol. 26, no. 9, pp. 4483–4498, Sep. 2017. doi: 10.1109/TIP.2017.2705424
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    Highlights

    • We use a gradient-based orientation field to obtain continuous orientation representations within an acceptable time-frame, and propose a double-orientation encoding method to make the orientation codes more accurate and stable.
    • We propose a window-based feature measurement, by which the process of position translations can be removed for speeding up the searching.
    • We evaluate the performance of accuracy and speed on two large-scale databases, namely, Hong Kong PolyU large-scale database and CASIA palmprint database plus a synthetic database. We compare the proposed method with existing hashing-based methods, as well as state-of-the-art palmprint identification approaches. The results demonstrate the obvious advantages of the proposed method over previous works.

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