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A new algorithm for number of holes attribute filtering of grey-level images

机译:灰度图像孔数属性滤波的新算法

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摘要

In this paper we present a new algorithm for filtering a grey-level image using as attribute the number of holes of its connected components. Our approach is based on the max-tree data structure, that makes it possible to implement an attribute filtering of the image with linear computational cost. To determine the number of holes, we present a set of diverse pixel patterns. These patterns are designed in a way that the number of holes can be computed recursively, this means that the calculations done for the components of the image can be inherited by their parent nodes of the max-tree. Since we do not need to re-calculate the attribute data for all connected components of the image, the computation time devoted to the attribute computation remains linear.
机译:在本文中,我们提出了一种新算法,该算法使用连接的组件的孔数作为属性来过滤灰度图像。我们的方法基于最大树数据结构,这使得以线性计算成本实现图像的属性过滤成为可能。为了确定孔的数量,我们提出了一组不同的像素图案。这些模式的设计方式是可以递归计算孔的数量,这意味着可以通过max-tree的父节点继承对图像成分进行的计算。由于我们不需要为图像的所有连接的分量重新计算属性数据,因此用于属性计算的计算时间保持线性。

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