Blood Smear Image Based Malaria Parasite and Infected-Erythrocyte Detection and Segmentation
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In this study, an automatic malaria parasite detector is proposed to perceive the malaria-infected erythrocytes in a blood smear image and to separate parasites from the infected erythrocytes. The detector hence can verify whether a patient is infected with malaria. It could more objectively and efficiently help a doctor in diagnosing malaria. The experimental results show that the proposed method can provide impressive performance in segmenting the malaria-infected erythrocytes and the parasites from a blood smear image taken under a microscope. This paper also presents a weighted Sobel operation to compute the image gradient. The experimental results demonstrates that the weighted Sobel operation can provide more clear-cut and thinner object contours in object segmentation.
KeywordsMalaria parasite Blood smear image Edge detection Image segmentation
MHT and YKC conceived the study. SSY designed the approach and performed the computational analysis with CCJ. MHT and YKC supervised the work and tested the program. MHT, SSY, YKC and CCJ wrote the manuscript. MHT prepared the samples and collected the data. MHT and YKC contributed analyzing experimental studies. All authors read and approved the final manuscript. YKC and SSY contributed equally and are the correspondents as well as listed in alphabetical order.
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