A fast segmentation scheme for white blood cell images

Presents a fast segmentation scheme for automatic differential counting of white blood cells. The segmentation procedure consists of three phases. First a novel simple algorithm is proposed for localization of white blood cells. The algorithm is based on a priori information about blood smear images. In the second phase the different cell components are separated with automatic thresholding. The thresholds are selected with a simple recursive method derived from maximizing the interclass variance between dark, gray and bright regions based on the method proposed by Otsu (1979). Finally the segmented regions are smoothed by morphological operations. The segmentation scheme works successfully for classification of white blood cells. Some experimental results are also presented.< >