## 4 Proposed Work
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Dataset**} & \multirow{2}{*}{**Image Size**} & \multicolumn{2}{c}{**No PS**} & \multicolumn{2}{c}{**SA**} & \multicolumn{2}{c}{**GA**} & \multicolumn{2}{c}{**MA**} \\ \cline{3-10}  & & **Feature Dimension** & **Accuracy Score (\%)** & **Feature Dimension** & **Accuracy Score (\%)** & **Feature Dimension** & **Accuracy Score (\%)** \\ \hline \multirow{3}{*}{JAFF} & 32\(\times\)32 & 640 & 67.53 & 323 & 66.23 & 375 & 79.22 & 377 & 84.42 \\ \cline{2-10}  & 48\(\times\)48 & 1440 & 72.73 & 704 & 68.83 & 910 & 80.52 & 836 & 84.42 \\ \cline{2-10}  & 64\(\times\)64 & 2560 & 71.43 & 1203 & 71.43 & 1541 & 81.82 & 1408 & 83.12 \\ \cline{2-10}  & 32\(\times\)32 & 640 & 90.49 & 320 & 83.21 & 400 & 93.28 & 429 & 94.03 \\ \cline{2-10}  & 48\(\times\)48 & 1440 & 95.71 & 683 & 91.60 & 851 & 98.32 & 894 & 98.88 \\ \cline{2-10}  & 64\(\times\)64 & 2560 & 98.51 & 1333 & 95.90 & 163 & 98.32 & 1414 & 98.75 \\ \hline \multirow{3}{*}{**Dataset**} & **Mean-BPSO** & **WAO-CM** & **LHCAA** & **SFHSA** & & & & \\ \cline{2-10}  & **Feature Dimension** & **Accuracy Score (\%)** & **Feature Dimension** & **Accuracy Score (\%)** & **Feature Dimension** & **Accuracy Score (\%)** & **Feature Dimension** & **Accuracy Score (\%)** \\ \hline \multirow{3}{*}{JAFF} & 301 & 84.03 & 217 & 79.22 & **319** & **84.42** & 197 & 81.82 \\ \cline{2-10}  & 701 & 84.42 & 630 & 83.12 & 767 & 83.12 & **560** & **92.21** \\ \cline{2-10}  & 1507 & 83.12 & 419 & 89.61 & 1425 & 83.12 & **818** & **90.91** \\ \hline \multirow{3}{*}{RAPD} & 344 & 92.36 & 557 & 93.74 & **337** & **94.59** & 241 & 91.91 \\ \cline{2-10}  & 770 & 95.52 & 1074 & 96.46 & **788** & **98.88** & 341 & 96.51 \\ \cline{2-10}  & 1300 & 98.13 & 1186 & 97.01 & **1271** & **99.25** & 462 & _97.79_ \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Performance of SFHSA with respect to No FS, SA, GA, MA, ME-BPSO, WAO-CM and LHCAA for Gabor filter-based features. \begin{table}
\begin{tabular}{l l l l l l l l l l l} \hline \hline  & & \multicolumn{4}{c}{**WAO-CM**} & \multicolumn{4}{c}{**LHCMA**} & \multicolumn{4}{c}{**SHHSA**} \\ \hline \hline \multirow{2}{*}{**Dataset**} & \multirow{2}{*}{**Image Size**} & \multirow{2}{*}{**Precision**} & \multirow{2}{*}{**Recall**} & \multirow{2}{*}{**F-Measure**} & \multirow{2}{*}{**Precision**} & \multirow{2}{*}{**Recall**} & \multirow{2}{*}{**F-Measure**} & \multirow{2}{*}{**Precision**} & \multirow{2}{*}{**Recall**} & \multirow{2}{*}{**F-Measure**} & \multirow{2}{*}{**Precision**} & \multirow{2}{*}{**Recall**} & \multirow{2}{*}{**F-Measure**} \\ \cline{3-3} \cline{5-10}  & & \multirow{2}{*}{**Image Size**} & & & & & & & & & \\ \hline \multirow{4}{*}{JAFFE} & \(32\times 32\) & 0.797 & 0.792 & 0.794 & **0.847** & **0.844** & **0.845** & 0.821 & 0.818 & 0.819 \\  & \(48\times 48\) & 0.827 & 0.831 & 0.831 & 0.836 & 0.831 & 0.833 & **0.927** & **0.922** & **0.924** \\  & \(48\times 64\) & 0.898 & 0.896 & 0.897 & 0.827 & 0.831 & 0.830 & **0.913** & **0.909** & **0.910** \\  & \(32\times 32\) & 0.939 & 0.937 & 0.938 & **0.949** & **0.946** & **0.946** & 0.923 & 0.919 & 0.920 \\ \cline{1-1}  & \(48\times 48\) & 0.971 & 0.965 & 0.968 & **0.991** & **0.989** & **0.989** & 0.973 & 0.965 & 0.966 \\ \cline{1-1}  & \(64\times 64\) & 0.968 & 0.970 & 0.969 & **0.989** & **0.992** & **0.990** & 0.986 & 0.978 & 0.982 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Performance of SFHSA with respect to WAO-CM and LHCMA for Gabor-based features in terms of Precision, Recall and F-measure.