Abstract
The disease, Malaria, is caused by Plasmodium Parasite, and is transmitted
via female Anopheles mosquito bite. There are 4 variants of plasmodium which cause
malaria, they are, 1) Plasmodium falciparum, 2) Plasmodium vivax, 3) Plasmodium
ovale, and 4) Plasmodium malariae. Though there are several clinical and laboratory
techniques for finding the presence of malaria, the accuracy and the time required to
determine the presence of the parasite are inadequate. Therefore, in this work, we have
come up with a system that uses image-processing techniques to determine the
presence of malaria in Human RBCs. In addition, the system determines the severity
and stage of the malarial parasite.
Malaria is brought on by the Plasmodium parasite and spread via female Anopheles
mosquito bites. Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale, and
Plasmodium malariae are the four plasmodium species that cause malaria. Although
there are a number of clinical and laboratory methods for detecting the presence of
malaria, the speed and precision needed to do so are insufficient. As a result, in this
study, we have developed a system that employs image-processing methods to
ascertain if there is malaria present in human RBCs. The technique also establishes the
malarial parasite's stage and intensity.
Keywords: Greyscale, Image processing, Malaria, Thresholding.