Malaria is a vector borne disease widely occurring at equatorial region. Even after decades of campaigning of malaria control, still today it is high mortality causing disease due to improper and late diagnosis. To prevent number of people getting affected by malaria, the diagnosis should be in early stage and accurate. This paper presents an automatic method for diagnosis of malaria parasite in the blood images. Image processing techniques are used for diagnosis of malaria parasite and to detect their stages. The diagnosis of parasite stages is done using features like statistical features and textural features of malaria parasite in blood images. This paper gives a comparison of the textural based features individually used and used in group together. The comparison is made by considering the accuracy, sensitivity, and specificity of the features for the same images in database.

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Malaria is caused due to the mosquito bite hence the parasite enter into blood through the saliva of the mosquito. The malaria parasite directly infects the red blood cells, therefore to design an automatic detection system, the red blood cells should be segmented from the artifacts and background in a microscopic image. Here in this paper watershed transform is used with the distance transform which separates even the overlapped red blood cells more efficiently, which are useful for the diagnosis of parasite and for the parasitemia too. The result shows improvement in diagnostic accuracy of detection of the parasite in Red Blood Cells and also describing the life cycle stage of the parasite. The accuracy, sensitivity and specificity achieved were as 97.7%, 97.4% and 97.7% respectively.