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Statistical color texture descriptors for histological images analysis

机译:统计颜色纹理描述符用于组织学图像分析

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In this paper we compare different approaches to combine color and statistical texture descriptors. Previous studies on this topic were conducted on natural images only. We focus on the particular case of histological datasets where color plays an important role due to the staining process of the biological samples. We also introduce two new variants of the well-known Local Binary Patterns (LBP) operator. We test these approaches on three diversified histological datasets. We show that combining color and texture features extracted separately is preferable on datasets having a large variability in the staining, while simultaneous extraction of color and texture information is recommended only for more standardized stainings.
机译:在本文中,我们比较了将颜色和统计纹理描述符组合在一起的不同方法。以前有关此主题的研究仅在自然图像上进行。我们关注组织学数据集的特殊情况,其中颜色由于生物样品的染色过程而起着重要的作用。我们还介绍了著名的本地二进制模式(LBP)运算符的两个新变体。我们在三个不同的组织学数据集上测试了这些方法。我们表明,结合使用单独提取的颜色和纹理特征,对于在染色中具有较大变异性的数据集而言,是比较可取的,而仅建议将颜色和纹理信息同时提取仅用于更标准化的染色。

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