An Efficient Image Processing Technique to Count Red Blood Cells

Abstract

Shortage of red blood cells (RBC), that constitutes 99 percent of blood cells and specialized as oxygen carrier, causes various blood disorders. The RBC is the important parameter while diagnosis and pathological study. Here, we create a system to detect to count the number of RBC in the blood smear image. The process is initiated by image acquisition and image enhancement where noise is removed from the images and the edges are preserved to converting to binary images thus separating the region of interest from the background. Further, by segmentation process we differentiate RBC from the various other components in the blood. Morphological operations are applied on the blood image followed by RBC counting using Hough transform which is an efficient image segmentation technique. The primary goal of the proposed system is to detect and count all the RBC including the overlapping one in the blood smear image.