Acta Photonica Sinica, Volume. 53, Issue 9, 0910004(2024)

OCT Internal and External Fingerprint Extraction Method Based on Soft Label

Yilong ZHANG... Shengming ZHU, Haixia WANG*, Haohao SUN and Rui YAN |Show fewer author(s)
Author Affiliations
  • School of Computer and Science Technology, Zhejiang University of Technology, Hangzhou 310000, China
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    Figures & Tables(14)
    Optical schematic of SD-OCT system[27]
    OCT fingerprint data
    Overall process of the algorithm
    Labeling process
    Coordinate attention block[14]
    Network architecture of SLCA-UNet
    External fingerprint images generated by different algorithms
    Internal fingerprint images generated by different algorithms
    The DET curves of external and internal fingerprint
    • Table 1. Fingerprint reconstruction steps based on soft Label

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      Table 1. Fingerprint reconstruction steps based on soft Label

      Fingerprint reconstruction step based on the soft Label
      Input. B-scan: I(x,y,z),the predict result of the stratum corneum layer and viable epidermal layer: Pexternalx,y,z),Pinternalx,y
      Output. External fingerprint and Internal fingerprint
      Step1. x=1 800,y=500,z=1 400,t=1
      Step2. Initialize:External fingerprint =zeros([zx])Internal fingerprint=zeros([zx])
      Step3. for t in range(1,z+1):(1-1400 B-scan image)
      Step4. finger_external[t-1,:]=sum(I(:,:,t)*Pexternal(:,:,t),axis=0)/(sum(Pexternal(:,:,t),axis=0))
      Step5. finger_internal[t-1,:]=sum(I(:,:,t)*Pinterna(:,:,t),axis=0)/(sum(Pinternal(:,:,t),axis=0))
      Step6. t=t+1 (process the next B-scan image)
      Step7. External fingerprintl=normalize(External fingerprint), the external fingerprint was normalized to 0 to 255
      Step8. Internal fingerprint=normalize(Internal fingerprint), the internal fingerprint was normalized to 0 to 255
    • Table 2. NFIQ scores of different algorithms

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      Table 2. NFIQ scores of different algorithms

      Extraction methodFingerprintMean values of NFIQ 2.0 score
      ZAM 1External fingerprint18
      Internal fingerprint36
      ZAM 2External fingerprint28
      Internal fingerprint35
      ZAM 3External fingerprint14
      Internal fingerprint35
      U-NetExternal fingerprint31
      Internal fingerprint41
      GradientExternal fingerprint32
      Internal fingerprint42
      SLCA-UNetExternal fingerprint35
      Internal fingerprint47
    • Table 3. Time comparison of different algorithms

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      Table 3. Time comparison of different algorithms

      Extraction methodDenoising time/sExtraction time/s
      ZAM176 00091
      U-Net280127
      Gradient16 000580
      SLCA-UNet0140
    • Table 4. Results of the ablation experiments of each module

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      Table 4. Results of the ablation experiments of each module

      GroupMethodNFIQ 2.0 scoreEER scoreExtraction time/s
      External fingerprintInternal fingerprintExternal fingerprintInternal fingerprint
      1U-Net31411.1%1.5%127
      2UNet+Coordinate attention31441.2%1.2%140
      3U-Net+Soft Label34460.9%0.9%127
      4Our method(UNet+Soft Label+Coordinate attention)35470.8%0.8%140
    • Table 5. Experimental results for the contour boundaries are smooth or not

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      Table 5. Experimental results for the contour boundaries are smooth or not

      GroupMethodNFIQ 2.0 scoreEER score
      External fingerprintInternal fingerprintExternal fingerprintInternal fingerprint
      1Smooth contour boundary Label (our method)35470.8%0.8%
      2Unsmooth contour boundary Label253522.5%0.9%
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    Yilong ZHANG, Shengming ZHU, Haixia WANG, Haohao SUN, Rui YAN. OCT Internal and External Fingerprint Extraction Method Based on Soft Label[J]. Acta Photonica Sinica, 2024, 53(9): 0910004

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    Paper Information

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    Received: Jan. 25, 2024

    Accepted: Apr. 28, 2024

    Published Online: Nov. 13, 2024

    The Author Email: WANG Haixia (hxwang@zjut.edu.cn)

    DOI:10.3788/gzxb20245309.0910004

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