Malaria is a life-threatening disease which is caused by a Plasmodium parasite which is transmitted by infected mosquito’s bite. Similarly, Dengue fever is a very painful mosquito-borne disease caused by the dengue virus. Manual Detection of both of the diseases takes too much time and tropical and sub-tropical areas are experiencing these diseases at the high level and due to detection taking too long an automated system for detection of these diseases has become a need which consumes less time and cost. There are existing techniques for prediction of malaria using neural networks, multi-layer perceptron. Based on the survey in this paper we propose a system for prediction of malaria and dengue using image processing concepts such as segmentation techniques and morphological operations such as flood fill. In many laboratories, the blood cell count is done manually and needs to be done by an expert. This project uses a digital camera which works with a traditional microscope where the camera provides microscopic images to the computer. The proposed hardware is cost-efficient.