Robust leukocyte segmentation in blood microscopic images based on intuitionistic fuzzy divergence

Image processing-based analysis of microscopic leukocyte helps in early detection of many diseases. It is a challenging issue to segment leukocytes under uneven imaging conditions since features of microscopic leukocyte images change in different labratories. This paper introduces an automatic robust method to segment leukocyte from blood microscopic images using intuitionistic fuzzy divergence based thresholding. The method is constructed based on three simple assumptions which is common between blood microscopic images. To evaluate the robustness of proposed method, it has been tested on three dataset. Experimental results demonstrate that proposed approach effectively segment leukocytes from various type of blood microscopic images.

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