Analyzing blood cell image to distinguish its abnormalities (poster session)

In this paper, we show the blood-cell image classification system to be able to analyze and distinguish blood cells in the peripheral blood image. To distinguish their abnormalities, we segment red and white-blood cell in an image acquired from microscope with CCD camera and then, apply the various feature extraction algorithms to classify them. In addition to, we use neural network model to reduce multi-variate feature number based on PCA(Principal Component Analysis) to make classifier more efficient. Finally we show that our system has a good experimental result and can be applied to build an aiding system for pathologist.