I. Introduction

There are progressive advancements in medical imaging technology in the course of the most recent decades. It is the most significant advance in computational techniques in almost every field of image processing that outcome in the improvement in medical image. Image segmentation and pattern recognition technologies assume an essential part in computer-aided diagnosis, and have discovered a great deal of clinical applications. For differential blood count, accurate counting of number of Red Blood Cells (RBCs) or White blood Cells (WBCs) is a vital step [4]. In disease detection count and morphology of blood component is considered. Cell segmentation is a popular topic in biomedical image analysis. To check number of cells, cells ought to be segmented from data picture. Segmentation is the separation of image region of interest from the background. After cell segmentation blood components are analyzed. Study the properties of certain cells is necessary for detection of disease. Stained thin blood slides are utilized for image acquisition because it colorizes RBCs and stains WBCs and parasites if it present inside the blood cell. Images are captured by connecting high resolution camera to the microscope. Captured images are preprocessed for noise reduction and enhancement purpose [7].