A NOVEL APPROACH FOR RED BLOOD CELL COUNTING USING FUZZY C-MEANS SEGMENTATION (International Journal of Engineering Sciences & Management Research, 2014)
Red blood Cell count is a preliminary process in major applications related to disease diagnosing and medical research. This paperis the study of automated methods of cell counting processed through computational algorithms. HSV and Fuzzy C-Means (at 2ndstage) were efficient for processing of image. The input image of cell is cleaned and morphological operations are optimized togenerate the number of red blood cells. Results show the efficiency of algorithm over manual calculations in terms of minimizedtime frame and equivalent accuracy. The model was developed on virtual platform (MATLAB)..