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Figure 10(a) shows the distribution between genuine user and impostor to the smallest EER value classifier using WLPP, Figure 10(b) shows the ROC curve when implementing the system based on WLPP features vector with different classifier and Table 3 shows the EER value with different classifier methods.
Figures 10(a) and 10(b) and Table 3 show that the results based on WLPP features vector are almost acceptable because wavelet feature vector give useful information on the vein features as global feature vector and the LPP method remove all the redundancy features.
Figure 12(b) shows the ROC curve when implementing the system based on image enhancement and WLPP and LBPV_LPP features vector with different classifiers and Table 5 shows the EER value with different classifier methods.
WLPP extracted the global features to the vein images and when combined with LBPV_LPP local features give the best result in verification.
The main benefit of the proposed method is that which uses the combination of the local and global feature vectors (WLPP and LBPV_LPP) and uses the matching score fusion method that reaches to lowest EER value.
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- Wlodimierz Trzebiatowski
- Wlodzimierz Kurylowicz