## 4 The Proposed Finger Photo Color Net (FPCN)
### Results
Spoof finger photos displayed by a certain device, thus featured by certain saturation levels can be effectively represented by the HSV representation. CMY is the subtractive color of RGB, i.e., brighter colors in RGB color space are darker in CMY. This property is useful for discriminating printout attacks since most printouts are captured on white paper, which is a reflective (bright) material. The _time efficiency_ of the proposed PAD system was also computed. _Time efficiency_ indicates the time required by the system to be executed on the available resources [35; 36]. It is defined as the elapsed time from the moment the input data is captured until the decision is output [37]. The deep fusion module operating on six patches (one patch per color space) \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Model** & **EER\%** & **Avg. Accuracy** & **Standard Deviation** & **F1 Score** & **CV-10 fold** \\ \hline \multirow{8}{*}{Finger photo : Trained on all color spaces} & Alexnet & 6.97 & 92.5 & 1.52 & 0.91 & \(91.98\pm 1.04\) \\  & VGG16 & 8.08 & 90.4 & 1.57 & 0.89 & \(89.31\pm 0.96\) \\  & VGG19 & 6.42 & 93.6 & 1.41 & 0.85 & \(91.67\pm 1.84\) \\ \cline{2-6}  & ResNet 18 & 8.64 & 91.1 & 0.98 & 0.87 & \(91.61\pm 1.44\) \\ \cline{2-6}  & ResNet-34 & 6.12 & 93.9 & 1.64 & 0.84 & \(93.04\pm 1.25\) \\ \cline{2-6}  & GoogleNet & 7.84 & 92.6 & 0.94 & 0.89 & \(91.51\pm 0.98\) \\  & Dense-121 & 6.38 & 93.2 & 1.34 & 0.87 & \(92.51\pm 0.97\) \\ \hline \multirow{8}{*}{Finger photo : Trained on RHY} & Alexnet & 4.02 & 95.41 & 0.92 & 0.931 & \(95.47\pm 0.87\) \\  & VGG16 & 4.97 & 94.1 & 0.68 & 0.965 & \(94.45\pm 0.81\) \\ \cline{2-6}  & VGG19 & 6.42 & 93.93 & 0.91 & 0.85 & \(94.14\pm 1.24\) \\ \cline{2-6}  & ResNet 18 & 4.06 & 95.97 & 0.73 & 0.94 & \(94.14\pm 0.42\) \\ \cline{2-6}  & ResNet-34 & 3.54 & 96.65 & 0.67 & 0.95 & \(95.17\pm 0.87\) \\ \cline{2-6}  & GoogleNet & 4.09 & 96.08 & 0.65 & 0.96 & \(96.84\pm 1.04\) \\ \cline{2-6}  & Dense-121 & 3.01 & 97.1 & 1.48 & 0.97 & \(97.81\pm 0.48\) \\ \hline \multirow{8}{*}{Late Fusion: Selection of best nets} & RHYLXC & 0.964 & 97.42 & 1.63 & 0.969 & \(97.42\pm 1.04\) \\  & RHYXC & 0.961 & 97.27 & 0.98 & 0.953 & \(97.47\pm 0.64\) \\ \cline{1-1}  & RHYC & **0.841** & 98.91 & 1.01 & 0.964 & \(98.17\pm 1.20\) \\ \cline{1-1}  & RHY & **0.864** & 98.93 & 0.87 & 0.971 & \(98.37\pm 0.97\) \\ \hline \multirow{2}{*}{State of the art: Score-Level Fusion} & RHY [17] & 2.12 & 96.32 & 0.85 & 0.93 & \(97.28\pm 0.78\) \\ \cline{2-6}  & RHYL [17] & 2.71 & 96.81 & 0.98 & 0.95 & \(98.15\pm 0.87\) \\ \cline{1-1}  & RHYLX [17] & 3.29 & 96.02 & 1.03 & 0.91 & \(97.08\pm 0.95\) \\ \hline \multirow{8}{*}{State of the art: RGB Color Space} & LBP+SVM [4] & 3.02 & 97.7 & 0.85 & 0.98 & \(98.40\pm 0.74\) \\ \cline{1-1}  & DSIFT+SVM [4] & 5.03 & 95.05 & 0.27 & 0.96 & \(96.31\pm 0.21\) \\ \cline{1-1}  & LUCID+SVM [4] & 21.66 & 77.2 & 0.31 & 0.85 & \(78.34\pm 0.51\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of the Proposed Approach to the State-of-the-art in terms of EER%. Figure 7: **(a)** DET Curves illustrate the performance of late fusion on the overall system. **(b)** DET Curves illustrate the RHY finger photo patches trained on individual CNN. provides a global decision in 485 milliseconds. The total time efficiency when the fusion model provides a global decision by sequentially testing on five patches per subject is 2.6 s computed as 5 \(\times\) 485 ms added to the time to execute a majority voting. Additionally, the segmentation process with UNet takes 632 ms, while enhancement, minutia detection, and minutia patch extraction take a total of 14.35 s.  
The research performed a statistical test for a meaningful interpretation and comparison of the PAD methods analyzed in this study and their statistical differences. Table 5 reports [PERSON]'s test between the late fusion models. The results clearly show that the \(p\)-value is less than the significance value, i.e., 5%. our research also reports the \(\chi^{2}\) with 1 degree of freedom for all the late fusion models.