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Optimal Separable Algorithms to Compute the Reverse Euclidean Distance Transformation and Discrete Medial Axis in Arbitrary Dimension

机译:任意维反欧氏距离变换和中间轴离散的最优可分算法

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摘要

In binary images, the distance transformation (DT) and the geometrical skeleton extraction are classic tools for shape analysis. In this paper, we present time optimal algorithms to solve the reverse Euclidean distance transformation and the reversible medial axis extraction problems for d-dimensional images. We also present a d-dimensional medial axis filtering process that allows us to control the quality of the reconstructed shape
机译:在二进制图像中,距离变换(DT)和几何骨架提取是用于形状分析的经典工具。在本文中,我们提出了时间最优算法来解决d维图像的逆欧几里德距离变换和可逆中间轴提取问题。我们还提出了d维中间轴滤波过程,该过程使我们可以控制重构形状的质量

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