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Texture analysis using 3D Gabor features and 3D MPEG-7 Edge Histogram descriptor in fluorescence microscopy

机译:使用3D Gabor功能和3D MPEG-7 Edge直方图描述符进行荧光显微镜的纹理分析

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The recognition of patterns with focus on texture and shape analysis is still very hot topic, especially in biomédical image processing. In this article, we introduce 3D extensions of well-known approaches for this particular area. We focus on the collection of MPEG-7 image descriptors, specifically on the Edge Histogram Descriptor (EHD) and Gabor features, which are the core of the Homogeneous Texture Descriptor (HTD). The proposed extensions are evaluated on the dataset consisting of three classes of 3D volumetric biomédical images. Two different classifiers, namely k-NN and Multi-Class SVM, are used to evaluate the proposed algorithms. According to the presented tests, the proposed 3D extensions clearly outperform their 2D equivalents in the classification tasks.
机译:专注于纹理和形状分析的模式识别仍然是非常热门的话题,尤其是在生物医学图像处理中。在本文中,我们介绍了针对该特定领域的著名方法的3D扩展。我们专注于MPEG-7图像描述符的收集,特别是边缘直方图描述符(EHD)和Gabor功能,它们是同质纹理描述符(HTD)的核心。在由三类3D体积生物医学图像组成的数据集上评估了建议的扩展。两种不同的分类器,即k-NN和Multi-Class SVM,用于评估所提出的算法。根据提出的测试,在分类任务中,建议的3D扩展明显优于其2D等效项。

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