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A Streaming Distance Transform Algorithm for Neighborhood-Sequence Distances

机译:邻域序列距离的流距离变换算法

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We describe an algorithm that computes a “translated” 2D Neighborhood-Sequence Distance Transform (DT) using a look up table approach. It requires a single raster scan of the input image and produces one line of output for every line of input. The neighborhood sequence is specified either by providing one period of some integer periodic sequence or by providing the rate of appearance of neighborhoods. The full algorithm optionally derives the regular (centered) DT from the “translated” DT, providing the result image on-the-?y, with a minimal delay, before the input image is fully processed. Its efficiency can benefit all applications that use neighborhood- sequence distances, particularly when pipelined processing architectures are involved, or when the size of objects in the source image is limited.
机译:我们描述了一种使用查找表方法来计算“翻译的”二维邻域序列距离变换(DT)的算法。它要求对输入图像进行一次光栅扫描,并为每一行输入产生一行输出。通过提供某个整数周期序列的一个周期或通过提供邻居的出现率来指定邻居序列。完整算法可选地从“翻译的” DT中导出常规(居中)DT,从而在完全处理输入图像之前以最小的延迟即时提供结果图像。它的效率可以使所有使用邻域序列距离的应用程序受益,特别是在涉及流水线处理体系结构或源图像中对象大小受限制的情况下。

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