A NOVEL APPROACH FOR RED BLOOD CELL COUNTING USING FUZZY C - MEANS SEGMENTATION

Red blood Cell count is a preliminary process in major applications related to disease diagnosing and medical research. This paper is the study of automated methods of cell counting processed through computational algorithms. HSV and Fuzzy C - Means (at 2nd stage) were efficient for processing of image. The input image of cell is cleaned and morphological operations are optimized to generate the number of red blood cells. Results show the efficiency of algorithm over manual calculations in terms of minimiz ed time frame and equivalent accuracy. The model was developed on virtual platform (MATLAB).