Abstract
In order to resolve the problem of recognizing blood cancer cells accurately and effectively, an identifying and classifying algorithm was proposed using grey level and color space. After image processing, blood cells images were gained by using denoising, smoothness, image erosion and so on. After that, we use granularity analysis method and morphology to recognize the blood cells. And then, calculate four characterizes of each cell, which is, area, roundness, rectangle factor and elongation, to analysis the cells. Moreover, we also applied the chromatic features to recognize the blood cancer cells. The algorithm was testified in 100 clinical collected cases of blood cells images. The results proved that the algorithm was valid and efficient in recognizing blood cancer cells and had relatively high accurate rates on identification and classification.
