A leukocyte segmentation method based on S component and B component images is proposed. Threshold segmentation operation is applied to get two binary images in S component and B component images. The samples used in this study are peripheral blood smears. It is easy to find from the two binary images that gray values are the same at every corresponding pixels in the leukocyte cytoplasm region, but opposite in the other regions. The feature shows that "IMAGE AND" operation can be employed on the two binary images to segment the cytoplasm region of leukocyte. By doing "IMAGE XOR" operation between cytoplasm region and nucleus region, the leukocyte segmentation can be retrieved effectively. The segmentation accuracy is evaluated by comparing the segmentation result of the proposed method with the manual segmentation by a hematologist. Experiment results show that the proposed method is of a higher segmentation accuracy and it also performs well when leukocytes overlap with erythrocytes. The average segmentation accuracy of the proposed method reaches 97.7% for segmenting five types of leukocyte. Good segmentation results provide an important foundation for leukocytes automatic recognition.