Perceptual grouping in grey-level images by combination of Gabor filtering and tensor voting
Perceptual grouping in grey-level images by combination of Gabor filtering and tensor voting
复制标题
通过结合 Gabor 滤波和张量投票对灰度图像进行感知分组
DOI：
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发表时间：
2002
期刊：
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通讯作者：
B. Mertsching
中科院分区：
文献类型：
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作者：
A. Massad;M. Babós;B. Mertsching
我们提出了一种称为张量投票的感知分组方法的扩展，以应用于灰度图像。除了以前使用的由二值图像或边缘图组成的输入之外，我们还引入了局部取向张量的使用，该张量是通过应用于输入图像的一组Gabor滤波器来计算的。这种方法不仅产生面向输入的标记，而且产生连接的位置作为感知分组的输入。我们展示了如何将这种扩展平滑地嵌入到张量投票框架中，并在示例图像上演示了该方法。
We present the extension of a perceptual grouping method known as tensor voting to the application on grey-level images. In addition to formerly used inputs consisting of binary images or edgel maps, we introduce the use of local orientation tensors which are computed from a set of Gabor filters applied to the input image. This approach not only yields oriented input tokens but also the locations of junctions as input to the perceptual grouping. We show how this extension can smoothly be embedded into the tensor voting framework and demonstrate the method on example images.