## 3 Results
#### 3.1.2 Classification of the Images of the Ventral Side of Fresh and Open-Air Sun-dried  
In the next step of classification analysis, images of the ventral side of fresh and open-air sun-dried mint leaves were compared using models based on selected textures from individual color channels. Table 4 presents the results of distinguishing samples using selected textures extracted from images in color channels \(R\), \(G\), and \(B\). The obtained results were very successful. An average accuracy of 100% and values of Precision, Recall, F-Measure, and MCC of 1.000 were found in the case of each color channel as channels \(R\) and \(G\) for J48, and channel \(B\) for all KStar, JRip, and J48 algorithms. It proved the high differentiation of fresh and open-air sun-dried mint leaves in terms of selected textures belonging to color space RGB and thus the great influence of open-air sun drying on the structure of the outer surface of the mint leaves. Very high correctness of classification of fresh and open-air sun-dried mint leaves was also obtained for color channels \(L\), \(a\), and \(b\) from the color space Lab (Table 5). A completely correct classification with an average accuracy of 100% was observed in the case of models built based on selected texture parameters from images in color channels \(a\) and \(b\) for all algorithms (KStar, JRip, and J48). A slightly lower average accuracy reaching \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline \multirow{2}{*}{**Algorithm**} & \multicolumn{2}{c}{**Predicted Class (\%)**} & \multicolumn{2}{c}{**Average**} & \multirow{2}{*}{**Precision**} & \multirow{2}{*}{**Recall**} & \multirow{2}{*}{**F-Measure**} & \multirow{2}{*}{**MCC**} \\  & \multicolumn{2}{c}{**Fresh**} & & & & & & \\  & \multicolumn{2}{c}{**Shade-Dried**} & \multicolumn{2}{c}{**Actual Class**} & & & & & \\  & \multicolumn{2}{c}{**Color channel \(X\)**} & & & & & \\ \cline{2-7} lazy.KStar & 95 & 5 & Fresh & 95 & 0.950 & 0.950 & 0.950 & 0.900 \\  & 5 & 95 & Shade-dried & & 0.950 & 0.950 & 0.950 & 0.900 \\ rules.JRip & 100 & 0 & Fresh & & 0.952 & 1.000 & 0.976 & 0.951 \\  & 5 & 95 & Shade-dried & & 1.000 & 0.950 & 0.974 & 0.951 \\ trees.J48 & 95 & 5 & Fresh & & 1.000 & 0.950 & 0.974 & 0.951 \\  & 0 & 100 & Shade-dried & 97.5 & 0.952 & 1.000 & 0.976 & 0.951 \\  & \multicolumn{2}{c}{Color channel \(Y\)} & & & & & \\ lazy.KStar & 100 & 0 & Fresh & 1.000 & 1.000 & 1.000 & 1.000 \\  & 0 & 100 & Shade-dried & 100 & 1.000 & 1.000 & 1.000 & 1.000 \\ rules.JRip & 95 & 5 & Fresh & & 1.000 & 0.950 & 0.974 & 0.951 \\  & 0 & 100 & Shade-dried & & 0.952 & 1.000 & 0.976 & 0.951 \\ trees.J48 & 95 & 5 & Fresh & & 0.950 & 0.950 & 0.950 & 0.900 \\  & 5 & 95 & Shade-dried & 95 & 0.950 & 0.950 & 0.950 & 0.900 \\  & \multicolumn{2}{c}{Color channel \(Z\)} & & & & & \\ lazy.KStar & 100 & 0 & Fresh & 0.952 & 1.000 & 0.976 & 0.951 \\  & 5 & 95 & Shade-dried & 97.5 & 1.000 & 0.950 & 0.974 & 0.951 \\ rules.JRip & 100 & 0 & Fresh & & 0.952 & 1.000 & 0.976 & 0.951 \\  & 5 & 95 & Shade-dried & & 1.000 & 0.950 & 0.974 & 0.951 \\ trees.J48 & 95 & 5 & Fresh & & 0.950 & 0.950 & 0.950 & 0.900 \\  & 5 & 95 & Shade-dried & 95 & 0.950 & 0.950 & 0.950 & 0.900 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The performance metrics of distinguishing images of the ventral side of fresh and shade-dried mint leaves using selected textures from color channels \(X\), \(Y\), and \(Z\) from color space XYZ. 97.5% was determined for a model built using selected textures from color channels \(L\) and the J48 algorithm.