AUTOMATIC DETECTION OF MALARIA PARASITES FOR ESTIMATING PARASITEMIA: Review Paper
Keywords:
OTSU Thrsholding, Feature Extraction, SVM Classifier, Malaria, Android, SD card, Java, RBC, WBC, Annular Ring Ratio method, RGB to gray scale conversion, Trophozoite, Schizonts, GametocytesAbstract
This paper describes a fast and reliable mobile phone Android application platform for blood image analysis and
malaria diagnosis from Giemsa stained thin blood film images. The application is based on novel Annular Ring
Ratio Method which is already implemented, tested and validated in MATLAB. The method detects the blood
components such as the Red Blood Cells (RBCs), White Blood Cells (WBCs), and identifies the parasites in the
infected RBCs. The application also recognizes the different life stages of the parasites and calculates the
parasitemia which is a measure of the extent of infection. The main objective of the research is to successfully
implement the application on to the mobile platform without the loss of information integrity, with minimal memory
footprint on the mobile phone. In this paper, an attempt has been made to implement the malarial diagnosis
algorithm, that has already been implemented, tested and evaluated on a MATLAB platform into an Android mobile
phone. The main objective of the research is to successfully implement the application on to the mobile platform
without the loss of information integrity, with minimal memory footprint on the mobile phone.
