Red Blood Cell and Sickle Cell Detection from Microscopic Blood Images of Sickle Cell Anemic Patient

Abstract

Sickle cell anemia (SCA) is a type of haemolytic anemia which is the most commonly inherited blood disorder. Detection of red blood cell and sickle cell from sickle cell anemic person is a very challenging task. Besides traditional visual inspection of microscopic images, various methods have been developed which are based on image processing technique for faster and more accurate diagnosis of SCA. In this paper normal and abnormal red blood cells have been detected using Niblack’s thresholding technique from microscopic blood images of sickle cell anemic patient. The process involves preprocessing of microscopic blood smear and segmenting the preprocessed image using Niblack’s thresholding algorithm. Then using geometrical features of blood cells a metric (form factor) is calculated to classify normal red blood cells and abnormal cells.