Abstract: To solve the problem of low efficiency of leukocyte recognition in artificial microscopy, automatic recognition of white blood cells was studied on computer micro vision platform. After filtering the image color model, precise stripping of white blood cells and image background was realized by region growing algorithm. The extraction of nucleus and cytoplasm of leucocytes was realized by Otsu method, which is valley threshold segmentation method of gray histogram. According to the morphological, color and texture characteristics of cells, a large number of white blood cells were identified and classified by artificial neural network classifier. The results show that, white blood cell image segmentation and intelligent identification algorithm have high accuracy and efficiency. The final accuracy can reach 95.6%. It meets the need of automatic detection of leukocytes in clinical microscopic vision.