Red Blood based disease screening using marker controlled watershed segmentation and post-processing

Cell segmentation is a challenging problem due to the complexity and nature of the blood cells. Traditional methods of counting the cells are slow, error prone and often influenced by the performance of the operator. This paper aims to segment and count Red Blood Cells (RBCs) automatically shown in microscopic blood images to determine the condition of the person under examination. We also aim to increase the accuracy of segmentation by precisely looking into the counting of the overlapped cells which is the most conventional challenging task faced by many researchers. The RBCs in this paper are segmented using the integration of marker controlled watershed segmentation with morphological operations. The result of the proposed algorithm was validated with the manual counting method, and a good conformity of about 93.13 % was obtained. The future work will involve segmentation of more complex overlapping cells and the development of Smartphone based realtime disease screening system.