## 3 Results and Discussion
### Results Using Other Datasets  
The best results for the eye images and eyebrow images from the EYB dataset were first re-evaluated using the whole dataset to observe the effect of using the limited number of images vs. larger data. As mentioned before, in this research, the limited data set of EYB contained 434 images from 7 respondents, while the whole EYB dataset contained 2242 images from 38 respondents. The previous best results from the eye images were produced from \(SS+X\) and \(SS+H\), while from the eyebrow images, the best results were produced from \(A+H\) from the \(Sym2\) and \(Db2\) wavelets. Table 11 shows the limited data results vs. larger data using the EYB dataset. From Table 11, we observed that by using a larger number of images in the same dataset (EYB dataset), the accuracy results for the eye images showed higher performance, while the eyebrow images showed inferior results. Although the eyebrows feature produced higher performance, the eyes feature in the face images had the potential to be a more stable feature for a larger dataset. The effects of the limited and whole datasets were also evaluated against the ABD. From Figure 9, we observed that contradictory results were found. The limited ABD produced higher results than the whole ABD for the eye images and eyebrow images. We also assessed the same experimental conditions for the eye and eyebrow images using the PES datasets for the face images and RFFMDS v1.0 for the masked face images. Figure 9 displays the accuracy results from these datasets using \(SVM\)-\(1\). We observed that the whole EYB dataset produced the highest accuracy for the eye images, followed by the PES, RFFMDS v1.0, limited EYB, limited ABD, and whole ABD. The limited EYB dataset produced the best results for the eyebrow images, followed by RFFMDS v1.0, whole EYB, PES, limited ABD, and whole ABD. For the limited and whole ABD, the best results were obtained with \(SS+H\) at \(O=1\) and \(L=1\). In the PES dataset, the best results for the eye images were from \(A2\) with the \(Sym2\) and \(Db2\) wavelets, and the eyebrow images displayed the best results with \(SS+H\) at \(O=1\) and \(L=3\). For the RFFMDS v1.0 dataset, the best results for the eye images were obtained from \(SS\) at \(O=0\) and \(L=3\). The eyebrow images displayed the best results from \(A1\) with the _Haar_ wavelet. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Region**} & \multirow{2}{*}{**Method**} & \multicolumn{2}{c}{**Accuracy (\%)**} \\ \cline{3-4}  & & **Limited EYB (434 Images)** & **Whole EYB (2242 Images)** \\ \hline Eyes & base & 66.36 & 74.04 \\  & \(SS+H\) & 74.65 & 85.37 \\  & \(SS+X\) & 76.04 & 83.41 \\  & \(Sym2\)(A) + \(H\) & 74.65 & 96.88 \\  & \(Sym2\)(A) + \(X\) & 64.06 & 96.52 \\  & \(Db2\)(A) + \(H\) & 74.65 & 96.88 \\  & \(Db2\)(A) + \(X\) & 64.06 & 96.52 \\ \hline Eyebrows & base & 92.63 & 79.3 \\  & \(SS+H\) & 94.93 & 83.23 \\  & \(SS+N\) & 94.93 & 83.59 \\  & \(Sym2\)(A) + \(H\) & 98.16 & 83.59 \\  & \(Sym2\)(A) + \(X\) & 96.31 & 93.22 \\  & \(Db2\)(A) + \(H\) & 98.16 & 83.59 \\  & \(Db2\)(A) + \(X\) & 96.31 & 93.22 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: The accuracy (%) results of the limited EYB dataset vs. the whole EYB dataset against the best method in all proposed idea. It is worth noting the differences between these datasets. The ABD has more variations in showing respondents' conditions when capturing the images, such as variations in lighting conditions, facial expressions, and hair styles. Sometimes, the hairstyles of the respondents occluded the eye and eyebrow regions. The EYB dataset has little to no variations in the location of the eyes and eyebrows. The variations in the EYB dataset involve poses and illumination. Compared with the EYB dataset, the ABD has more uncontrolled conditions. The PES dataset has variations in respondents' expressions, resulting in more variations in eye and eyebrow shape, but they have fixed locations. Compared with the ABD, the PES dataset has more controlled conditions.