为了解决血细胞图像中白细胞与其它细胞色彩接近、亮度不均匀等问题, 采用了一种基于C-Y颜色空间的白细胞分割方法, 将原来的RGB图像转化为C-Y图像, 分离C-Y图像获得包含全部信息的B-Y颜色分量图像, 再根据连通域面积筛选、开运算、像素点操作得到完整的白细胞图像; 提取对比度拉伸后的G图像, 阈值分割得到细胞核的大概位置, 再用连通域面积筛选、开运算方法分割出完整的细胞核图像。结果表明, 本文中的算法对嗜酸性粒细胞、淋巴细胞、单核细胞和嗜中性粒细胞图像都具有较好的分割精度, 分别取得了94.33%, 91.60%, 97.72%, 98.66%的准确率。本文中的算法能较完整地分割出白细胞, 为后续分类研究奠定了基础。

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.