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Blood is made up of three main components; erythrocytes, leukocytes and thrombocytes. Each of these blood components all have their own roles in the human body. Leukocytes, which can be divided into five types; Basophil, Neutrophil, Eosinophil, Lymphocytes and Monocytes are all part of the body’s defence mechanism to fight against pathogens that could harm the body. Identifying the presence of these blood cells is one of the fundamental ways to diagnose a disease. Hence, blood tests are always being run by physicians in clinical practice. Manually identifying leukocytes is a tedious and time-consuming process, and does not guarantee standardised results as it depends fully on the operator’s skills. Therefore, many works have been done to develop an automated method of leukocyte identification, which aims to reduce the processing time, cost-effective and is efficient in producing standardised results. The proposed method uses the technique of segmenting the nucleus and cytoplasm of leukocytes by extracting it from the Saturation level of the image.