# Staining-Independent Malaria Parasite Detection and Life Stage Classification in Blood Smear Images
## 4 Experimental Results
Next, the second malaria parasite detection results are for the MBB dataset using different preprocessing methods when each input color image was converted into the grayscale space, and then the corresponding grayscale image was preprocessed by 1 of the 5 methods. Table 3 shows a general decline in the performance of all methods compared to that shown in Table 2, notably the precision and accuracy. Among them, the performances using the CLAHE for preprocessing had the most significant performance decrease. The use of contrast stretching for preprocessing maintained relatively stable performance across both sets of results, with only minor variations. Anyhow, the CLAHE yielded the best overall performance in terms of the precision, F1-score, and accuracy. Its performance on the recall was also among the highest. For the median blur and the CLAHE then contrast stretching preprocessing methods, they also performed well, particularly in the recall and F1-score, showing their potential to be good alternatives to the CLAHE. All in all, the results suggested that using \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{2}{c}{**MP-IDB (_P. malariae_) Dataset**} & **Precision** & **Recall** & **F1-Score** & **Accuracy** \\ \hline \multirow{4}{*}{Direct cropping} & Red blood cell & 1.00 & 1.00 & 1.00 & \\  & Ring & 0.98 & 0.94 & 0.96 & \\  & Prohozoite & 0.85 & 0.97 & 0.91 & 0.94 \\  & Schizont & 0.95 & 0.78 & 0.86 & \\  & Gametocyte & 0.92 & 1.00 & 0.95 & \\ \hline \multirow{4}{*}{Zero padding} & Red blood cell & 0.96 & 1.00 & 0.98 & \\  & Ring & 0.88 & 0.87 & 0.89 & \\  & Prohozoite & 0.87 & 0.84 & 0.81 & 0.88 \\  & Schizont & 0.88 & 0.67 & 0.79 & \\  & Gametocyte & 0.87 & 0.98 & 0.92 & \\ \hline \multirow{4}{*}{Cropping with background} & Red blood cell & 1.00 & 0.99 & 1.00 & \\  & Ring & 0.87 & 0.92 & 0.89 & \\ \cline{1-1}  & Prohozoite & 0.90 & 0.96 & 0.93 & 0.94 \\ \cline{1-1}  & Schizont & 0.87 & 0.92 & 0.89 & \\ \cline{1-1}  & Gametocyte & 0.98 & 0.95 & 0.97 & \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Malaria parasite life stage classification results on MP-IDB (_P. malariae_) dataset. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{2}{c}{**MP-IDB (_P. falciparum_) Dataset**} & **Precision** & **Recall** & **F1-Score** & **Accuracy** \\ \hline \multirow{4}{*}{Direct cropping} & Red blood cell & 0.87 & 0.98 & 0.92 & \\  & Ring & 0.84 & 0.73 & 0.78 & \\  & Trophozoite & 0.86 & 0.84 & 0.85 & 0.91 \\  & Schizont & 0.99 & 0.99 & 0.99 & \\  & Gametocyte & 0.98 & 1.00 & 0.99 & \\ \hline \multirow{4}{*}{Zero padding} & Red blood cell & 0.99 & 0.99 & 0.99 & \\  & Ring & 0.83 & 0.78 & 0.80 & \\ \cline{1-1}  & Trophozoite & 0.81 & 0.85 & 0.83 & 0.91 \\ \cline{1-1}  & Schizont & 0.99 & 0.96 & 0.97 & \\ \cline{1-1}  & Gametocyte & 0.95 & 0.95 & 0.97 & \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Malaria parasite life stage classification results on MP-IDB (_P. falciparum_) dataset. the first approach, i.e., preprocessing each input color image in the color space and converting each output into a grayscale image, was a better choice. Hence, this approach was applied to the proposed detection method with the CLAHE as the preprocessing method throughout the rest of the experiments. It is very interesting that when the best trained model was applied to another dataset (MP-IDB) with different staining and image acquisition methods, the test results were still very promising. These results are not surprising because the results in Tables 2 and 3 are from the test images with the same staining and image acquisition methods as the training dataset (MBB). Meanwhile, the results in Table 4 are from another dataset (MP-IDB) with different staining and image acquisition methods from the training data. The proposed detection methods yielded an accuracy of 0.84 for _P. vivax_, 0.82 for _P. ovale_, 0.79 for _P. malariae_, and 0.92 for _P. falciparum_ on the MP-IDB dataset. Meanwhile, the F1-scores for these 4 species were 0.90, 0.89, 0.85, and 0.96, respectively. The accuracy for _P.