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Robust Leukocyte Segmentation in Blood Microscopic Images Based on Intuitionistic Fuzzy Divergence

机译:基于直觉模糊分歧的血微观图像鲁棒白细胞分段

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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.
机译:基于图像处理的微观白细胞的分析有助于早期发现许多疾病。在不均匀的成像条件下对白细胞进行白细胞是一个具有挑战性的问题,因为微观白细胞图像在不同的息虑带中的特征发生变化。本文介绍了一种自动稳健的方法,以使用基于直觉的模糊发散的阈值化从血微观图像分段白细胞。该方法是基于三种简单的假设构建,血微观图像之间很常见。为了评估所提出的方法的稳健性,它已经在三个数据集中进行了测试。实验结果表明,提出的方法有效地从各种血微观图像中分段白细胞。

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