The project presents the classifications and detection of acute myelogenous leukemia in blood microscopic images using supervised classifiers. AML is a fast-growing cancer of the blood and bone marrow Input blood microscopic image is converted into gray scale for better features extraction. Then the segmentation process is done by k-means clustering method The system will be used to classify the queried images automatically to decide the abnormality.The performance of the system is evaluated through sensitivity, specificity and accuracy. White cell composition of the blood reveals important diagnosis information about the patients as well as patient follow-up. The haematologist requires two types of blood count for diagnosis and screening. The first one is called the Complete Blood Count (CBC) and the second one is called the Differential Blood Count (DBC). CBC could be done by instruments called cytometer and could successfully be performed automatically. On the other hand, DBC is more reliable but currently it is a manual procedure to be done by hematology experts using microscope In DBC, an expert counts 100 white blood cells on the smear at hand and computes the percentage of occurrence of each type of cell counted. The results reveal important information about patient's health status.