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文章基本信息

  • 标题:A Streaming Distance Transform Algorithm for Neighborhood-Sequence Distances
  • 本地全文:下载
  • 作者:Nicolas Normand ; Robin Strand ; Pierre Evenou
  • 期刊名称:Image Processing On Line
  • 电子版ISSN:2105-1232
  • 出版年度:2014
  • 卷号:4
  • 页码:196-203
  • 出版社:Image Processing On Line
  • 摘要:

    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-fly, 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.

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