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Dengue is considered as one of the viral disease that affects the human health in various countries. The dengue virus spreading through mosquitoes is treated as a rapid spreading virus that may even lead to death of a human. Hence, it is very essential to develop a quick diagnostic system that accurately finds the dengue by counting the red blood cells (RBC), White Blood Cells (WBC) and platelets from a microscopic image acquired from a human blood. In this paper, an automated blood image processing technique is developed with Multi Support Vector Machine Classifier (MSVM) that accurately finds the RBC, WBC and platelet count from a microscopic blood sample image. The detection of these three parameter provides an effective analysis on dengue symptoms from human body. The simulation via Matlab shows that the proposed MSVM classification engine provides faster and accurate classification on blood symptoms than other existing mechanisms.
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