Proper Diagnosis and Automation System for Detection of Malaria Infected Blood Cells in a Microscopic Images of a Blood

Malaria is a mosquito-borne disease mainly caused by the plasmodium parasites carried by a mosquitoes of Anopheles genus. Mainly there are five kinds of Plasmodium parasites namely plasmodium falciparum, plasmodium vivax, plasmodium malariae, plasmodium ovale and plasmodium knowlesi. Malaria infection will be identified mainly by patient’s symptoms and by testing the blood samples. Whereas symptoms will gives intimation about the disease but it will be confirmed only after proper testing. But the limitations is that if the malaria infected patient belongs to rural areas then for testing the blood expertized person is required to diagnose the blood and also if he is available, he may take two or three days to give the reports depending on the patients he need to handle. Since because of microscopic images contains very minute things, technician must be free from eye site. Also every processes involved will be manual and hence chances of getting error report will be more. Even the person in the urban areas will also have to face many problems such as they have to pay more money to diagnostic centres and also some amount of time required to get the report. By considering all this conditions the problem will be solved by proper diagnosis and by implementing an automation system for processing the microscopic images of blood. All this will be set and done by employing a MATLAB software and Image processing (segmentation) to process the image and to count the number of cells infected. To achieve this, automation process will involve the multi-thresholding of Otsu’s method for proper diagnosis and for counting the total number of infected cells will be carried out using watershed algorithm and connected component extraction.