Description

Image processing for detection of dengue virus based on WBC classification and decision tree

In this project,is dengue detection using image processing. A white blood cells classification was done using image processing to apply the detection of dengue virus.Dengue is a major health problem in tropical and Asia-Pacific regions which typically spreads rapidly in number of infection patients. Knowing that most of the world’s population living in risk areas, in order to diagnose and treat the disease, high skilled experts and human resources are needed. However, in some cases human error potentially may occur. Therefore, in this paper we developed a model which can diagnose dengue fever disease. This study used blood smear images that were taken under a digital microscope with images magnification specifications by means of image processing techniques such as color transformation, image segmentation, edge detection feature extraction and white blood cells classification. In this study we used white blood cell counting of the role of cell differentiation as a new feature that can classify dengue viral infections of patients via decision tree methods. The results showed that, the white blood cells classification modeling technique gives high accuracy.