White blood cell segmentation based on RGB and C-Y color space

In order to solve the problems of color approximation and uneven brightness between white blood cells and other cells in blood cell images, a white blood cell segmentation method based on C - Y color space was adopted. The original RGB image was transformed into C - Y image. C - Y image was separated to obtain B - Y color component image with all information. Secondly, a complete white blood cell image is obtained by screening the area of the connected region, opening operation and pixel operation. The contrast stretched G image was extracted. The approximate position of nucleus was obtained by threshold segmentation. And then, the complete nuclear image was segmented by area screening and open operation of connected domain. The results show that the algorithm in this paper has good segmentation accuracy for eosinophils, lymphocytes, monocytes and neutrophils, i.e., 94.33%, 91.60%, 97.72% and 98.66% respectively. The algorithm in this paper can segment white blood cells more completely. It lays a foundation for the follow-up classification research.