Comparison of SURF and HOG extraction in classifying the blood image of malaria parasites using SVM

Malaria is the deadliest disease caused by a protozoa parasite of the Plasmodium genus that is transmitted through the female Anopheles mosquito. Five Plasmodium species can cause infections and deaths such as P. Ovale, P. Malaria, P. vivax, and P. falciparum, each parasitic malaria pattern in the blood image has a unique and distinct pattern. The introduction of the parasitized pattern and uninfected cells conducted in this study used the extraction of surf and HOG features as well as SVM as methods classification. Research results show that SVM with SURF feature extraction can classify the parasitized pattern and uninfected cells in the blood image better than SVM with the extraction of HOG features. The average accuracy feature extraction of the SURF 85.83% while HOG feature extraction is only 83.50%.