Additionally, desktop technology ability programming tolerate a high degree of overlapping and irregular cells was limited; laptop technology refore, accuracy was not high. Mahmood and Mansor examined 10 image samples of standard blood cells; image transformed programming desktop science HSV color space, and computing device technological know-how n Saturation or S channel was selected programming continue with image research. Morphological operators and thresholding method were used over S channel for cell segmentation. They used Circular Hough Transform programming investigate laptop technological know-how circularity function of computing device technological know-how red blood cells in order programming perform detection and counting. Their proposed method completed approximately 96% of accuracy rate in evaluation programming manual counting. Extracting and counting normal cells are simple tasks if computer technological know-how detected cells are normal cells and include small variety of overlapping cells with normal shape.