MALARIA PARASITE DETECTION WITH THE HELP OF IMAGE PROCESSING AND MACHINE LEARNING

Abstract: Malaria is caused by “female Anopheles” mosquito. Mosquito transmits the Plasmodium Parasite to the blood which causes Malaria. The conventional method to diagnosis malaria is to examination of blood cell of patient in the microscope. The blood cell to be tested is kept in a slide then, observe the infected RBC under the microscope. This process consumes more time and expensive. Here we construct the image processing system detection and later we develop a machine learning code to detect the infected cells. We find out the accuracy using Keras-Sequential Model. In our project we will get the fast and accurate result. We try the keras model using SVM classifier. SVM have a positive rate of 99.8% in the detection of the plasmodium infected. Below average people living in village areas who lack of access to health care are at the greater risk for the disease. World Health Organization estimates that the India has a 15 million cases of the malaria with 19,500-20,000 deaths annually.

Keywords: Plasmodium, Machine Learning, Female Anopheles, Parasite