Manual examination on microscopic blood smears are being using by microscopists to detect and classify the malaria parasites. But sometimes manual inspection trapped with error because it rely on human abilities and experiences. Thus, an automatic detection and classification of Malaria Parasite is needed to reduce the misdiagnosis. This research is proposing a Morphological Threshold Area Estimation to help the microscopist in this process. The Morphological operation is used to filter the noise, shape simplification, and boundaries extraction. Then, threshold value estimation is done to obtain the suitable value in distinguish between Red Blood cell and the Malaria Parasite cell. Area detection process is done in classifying the types of Malaria Parasite either Ring, Schizont or Trophozoite type Malaria. From the analysis done, it shows that the proposed technique achieve 80% in accuracy in detecting and classifying the Malaria Parasite.
Volume 12 | 02-Special Issue