Color Based Segmentation of White Blood Cells in Blood Photomicrographs Using Image Quantization

Abstract

Generally for various diseases blood is used as an indicator. It is composed of three types of cells; Red blood Cells (RBC), White Blood Cells (WBC) and Platelets. Different types of white blood cells or leukocytes are counted in a sample blood smear and give necessary information about various hematological diseases. Evaluating a blood smear for WBC’s with the help of digital image processing is faster, easier and has contributed strongly in Computer Aided Diagnosis (CAD). In this work, we have focused on the segmentation of white blood cells in blood smear photomicrographs and proposed a novel technique for segmentation which can exploit color, size and shape features of different types of objects present in a blood smear photomicrographs.