Color Space Volume and Superpixel Based Leukocyte Image Segmentation

In this paper, we propose a novel method based on color space volume and multimodal histogram thresholding (MHT) for leukocyte segmentation in human blood smear images under the rapid staining condition. The proposed method first defines a new color space volume to highlight the leukocyte's nucleus region, and it then uses the MHT method to extract the nucleus. Then, the proposed method takes the central region in the superpixel segmentation result as an initial leukocyte region, and it then uses the MHT method to extract the leukocyte region. Finally, the cytoplasm is obtained by subtracting the nucleus region from the leukocyte region. Experimental results on a dataset containing 300 leukocyte images under rapid staining condition show that the proposed method provides a higher segmentation accuracy than the counterparts.