Machine learning approach for automated screening of malaria parasite using light microscopic images

► Staining variation has been removed from peripheral blood smear images. ► Impulse noise has been reduced. ► Erythrocytes are segmented using marker controlled watershed algorithm. ► Textural and morphological features have been extracted. ► Automated malaria infection (Plasmodium falciparum, Plasmodium vivax) stage recognition using pattern classification approach.