Blood Smear Image Based Malaria Parasite and Infected-Erythrocyte Detection and Segmentation. 
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.