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Fuzzy border distance transforms and their use in 2D skeletonization

机译:模糊边界距离变换及其在2D骨架中的应用

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Segmentation is always a difficult task in image analysis. In this paper we propose a solution to computing distance transforms in images with fuzzy object borders. The difference from a standard distance transform is in the initialisation, which takes the fuzziness of the border into account. As an example of its usefulness, the new fuzzy border distance transform is used in skeletonization.
机译:分段始终是图像分析中的困难任务。在本文中,我们提出了一种用模糊物体边界进行计算距离变换的解决方案。与标准距离变换的差异在初始化中,这将考虑到边界的模糊性。作为其有用性的一个例子,新的模糊边界距离变换用于骨架化。

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