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Laser & Optoelectronics Progress, Volume. 55, Issue 5, 051012(2018)

Palmprint and Palm Vein Feature Fusion Recognition Based on BSLDP and Canonical Correlation Analysis

Xinchun Li1; , Chunhua Zhang2*; *; , and Sen Lin1;
Author Affiliations
  • School of Electronic and Information Engineering, Liaoning Technical University, Huludao, Liaoning 125105, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (17)
    Equations (0)
    References (19)
    Cited By (3)
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    Paper Information
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    Figures & Tables(17)
    Kirsch operator in eight directions

    Fig. 1. Kirsch operator in eight directions

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    Sobel operator in eight directions

    Fig. 2. Sobel operator in eight directions

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    Sobel operator directional setting

    Fig. 3. Sobel operator directional setting

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    Edge response values

    Fig. 4. Edge response values

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    SLDP encoding example

    Fig. 5. SLDP encoding example

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    LDP and SLDP anti-noise tests. (a) Uninterrupted image; (b) image with noise

    Fig. 6. LDP and SLDP anti-noise tests. (a) Uninterrupted image; (b) image with noise

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    BSLDP histogram feature extraction

    Fig. 7. BSLDP histogram feature extraction

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    Overall block diagram of the system

    Fig. 8. Overall block diagram of the system

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    Actual acquisition device

    Fig. 9. Actual acquisition device

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    Image ROI example. (a) CASIA-M image database; (b) self-built non-contact image database

    Fig. 10. Image ROI example. (a) CASIA-M image database; (b) self-built non-contact image database

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    Result curves. (a) Matching result curve; (b) ROC curve

    Fig. 11. Result curves. (a) Matching result curve; (b) ROC curve

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    Result curves. (a) Matching result curve; (b) ROC curve

    Fig. 12. Result curves. (a) Matching result curve; (b) ROC curve

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    • Table 1. Basic situation of the experimental samples

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      Table 1. Basic situation of the experimental samples

      DatabaseCapturemethodLightsourceTestsample
      CASIA-MNon-contactWhite light /850 nm nearinfrared light6×100
      Self-builtnon-contactNon-contactWhite light /850 nm nearinfrared light5×100

    • Table 2. Number of matching

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      Table 2. Number of matching

      MatchingtypeCASIA-MdatabaseSelf-built non-contact database
      Intra-class15001000
      Inter-class178200123750

    • Table 3. EER with different blocks

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      Table 3. EER with different blocks

      ImageblockCASIA-M /%Self-built non-contact database /%
      1×15.349.04
      2×23.366.37
      4×42.082.82
      8×80.631.21
      16×161.321.78
      32×322.933.76

    • Table 4. Comparison of EER between the proposed algorithm and other algorithms

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      Table 4. Comparison of EER between the proposed algorithm and other algorithms

      AlgorithmEER of CASIA-M database /%EER of self-built non-contact database /%
      PalmprintPalm veinPalmprintPalm vein
      2DGabor7.177.935.171.97
      SURF4.7710.64.893.10
      LBP6.858.207.598.11
      LDP4.987.016.227.43
      BSLDP0.821.032.162.53
      MMNBP1.34 (fusion)3.09 (fusion)
      Ref. [10]0.75 (fusion)1.52 (fusion)
      Ref. [20]1.07 (fusion)1.56 (fusion)
      Proposed algorithm0.63(fusion)1.21 (fusion)

    • Table 5. Comparison of recognition time between the proposed algorithm and other algorithms

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      Table 5. Comparison of recognition time between the proposed algorithm and other algorithms

      AlgorithmRecognition time of CASIA-M database /sRecognition time of self-built non-contact database /s
      PalmprintPalm veinPalmprintPalm vein
      2DGabor0.09720.16310.12150.2594
      SURF0.10620.24570.25330.3630
      LBP0.01990.04340.07150.1037
      LDP0.08470.10810.10080.1236
      BSLDP0.05030.06100.05970.0812
      MMNBP0.1060 (fusion)0.1251 (fusion)
      Ref. [10]0.1670 (fusion)0.1904 (fusion)
      Ref. [20]0.1039 (fusion)0.1503 (fusion)
      Proposed algorithm0.0765 (fusion)0.1024 (fusion)
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    Xinchun Li, Chunhua Zhang, Sen Lin. Palmprint and Palm Vein Feature Fusion Recognition Based on BSLDP and Canonical Correlation Analysis[J]. Laser & Optoelectronics Progress, 2018, 55(5): 051012

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    Paper Information

    Category: Image processing

    Received: Sep. 29, 2017

    Accepted: --

    Published Online: Sep. 11, 2018

    The Author Email: Chunhua Zhang ( 1226617885@qq.com)

    DOI:10.3788/LOP55.051012

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology