Image Processing and Analysis can be defined as the act of examining images for the purpose of identifying objects and judging their significance. In current days, image processing techniques are widely used in many medical areas for improving earlier detection and treatment stages. The microscopic images of the blood cells are observed to find out many diseases. Changes in the blood condition show the development of diseases in an individual. Leukemia can lead to death if it is left untreated. Leukemia is detected only by analyzing the white blood cells. So our study is focused only on the white blood cells (WBCs). In a manual method of Leukemia detection, experts check the microscopic images. This is lengthy and time taking process which depends on the person’s skill and not having a standard accuracy. In this paper we are focusing, automated approach of leukemia detection. The automated Leukemia detection system analyses the microscopic image it extracts the required parts of the images and applies some filtering techniques. K-means clustering approach is used for white blood cells detection.

Segmentation, filtering techniques, K-Means clustering algorithm

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