# Evaluation of a Vein Biometric Recognition System on an Ordinary Smartphone
## 4 Implementation and Evaluation of the Recognition System
### Implementation Decisions and Performance Results  
The images acquired from the smartphone camera have a resolution of 1080 \(\times\) 1080 pixels but were rescaled to 300 \(\times\) 300 pixels to improve the execution time of the recognition algorithms. The results of the recognition performance in terms of EER values obtained with the MC and SIFT algorithms are shown in Table 1. Matching comparisons for each separated condition were performed by following the FVC (fingerprint verification competition) protocol, i.e., genuine comparisons were performed by comparing each sample to all  
Figure 5: (**a**) Biometric recognition process implemented in this work. Wrist result examples of (**b**) acquisition, (**c**) preprocessing, (**d**) SIFT feature extraction, and (**e**) postprocessing. the remaining samples from the same individual, and the impostor comparisons were performed by comparing the first sample of each individual to the first sample of all the remaining individuals. For all conditions, genuine comparisons included all the possible comparisons and impostor comparisons were performed by comparing the first sample of each individual under each condition to the first sample of all the remaining individuals under all the conditions. In all cases, symmetrical comparisons were removed. Table 2 compares our results with the other studies included in Section 2, which also acquire images of veins from smartphones and employ MC and SIFT algorithms. It should be noted that specific smartphones with near-infrared cameras were employed for the UC3M-CV2 database [7]. In the case of [10], an add-on module for smartphones was employed to supply an external light source. Furthermore, the smartphone was modified to remove the NIR blocking filter. From these results, a first conclusion is that similar recognition rates can be achieved with our proposal, even employing standard cameras and no additional light sources. From the results in Table 1, several conclusions can be obtained with respect to the body parts employed to locate veins, the acquisition conditions, and the algorithms considered. Regarding the body part, the results with wrists were somewhat better than with dorsal hands. We noticed that acquisition of wrist images was maybe easier for the users. Regarding the acquisition conditions, indoor conditions with light provided the best results. The results at indoor natural light 1 and 2 were similar except for dorsal hands and MC, where the results are better for indoor natural light 2, improving clearly for MC. The reason for this is that for indoor natural light 2, recognition is not only based on vein features extracted from the ROI, but also on features from the foreground associated with \begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Condition** & **Body Part** & **MC** & **SIFT 1** & **SIFT 2** & **SIFT 3** \\ \hline \multirow{2}{*}{Outdoor} & Wrist & 15.00 & 5.64 & 6.00 & 5.50 \\  & Dorsal Hand & 16.26 & 6.00 & 5.00 & 3.76 \\  & Wrist & 9.80 & 2.35 & 1.31 & 0.63 \\  & Dorsal Hand & 14.21 & 3.87 & 4.45 & 2.87 \\  & Wrist & 10.90 & 2.50 & 0.92 & 1.00 \\  & Dorsal Hand & 9.83 & 3.99 & 1.28 & 0.50 \\  & Wrist & 10.18 & 3.73 & 3.39 & 2.82 \\  & Dorsal Hand & 14.70 & 6.60 & 4.60 & 1.70 \\  & Wrist & 7.87 & 5.37 & 3.08 & 1.43 \\  & Dorsal Hand & 11.78 & 4.62 & 5.93 & 5.80 \\  & Wrist & 32.81 & 20.92 & 19.27 & 16.80 \\
**All** & Dorsal Hand & 30.74 & 21.90 & 20.96 & 19.30 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: EER values (%) obtained for the database acquired. \begin{table}
\begin{tabular}{l c c c} \hline \hline
**Body Part (Proposal)** & **Algorithm** & **Best EER (\%)** & **Worst EER (\%)** \\ \hline \multirow{2}{*}{Wrist (This work)} & MC & 7.87 & 32.81 \\  & SIFT 3 & 0.63 & 16.80 \\  & MC & 9.83 & 30.74 \\  & SIFT 3 & 0.50 & 19.30 \\  & SIFT 1 & 6.82 & 18.72 \\  & MC & 4.13 & 24.30 \\  & SIFT 4 & 10.63 & 41.12 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison to other proposals in the literature in terms of best and worst EER values.