A novel technique to diagnose malaria using image processing

Malaria is an infectious disease which has caused serious problems in regard to human health. In order to control and cure Malaria, we need the correct diagnosis and required treatments. In the present report, we present a new automatic method for diagnosing Malaria and its parasite by using an image processing technique and nervous system. In this method, we started with pre-processing to separate the red globules from the image with the help of an active contour model. Then by using wavelet function, we separated 840 features from the image. Afterward, with the advantage of vector supporting machine, we categorized the globules into normal and abnormal. In comparison to the past, the process of diagnosis improved and we have reached the result of 99.78%. In the pre-processing level, the noiser which has been recognized for categorization of red globules separated from the choice and then by using wavelet, we extract the features. We have tested and analyzed the data by using some nervous system and vector supporting machine.