A Streaming Distance Transform Algorithm for Neighborhood-Sequence Distances
Nicolas Normand, Robin Strand, Pierre Evenou, Aurore Arlicot
published
2014-09-01
reference
Nicolas Normand, Robin Strand, Pierre Evenou, and Aurore Arlicot, A Streaming Distance Transform Algorithm for Neighborhood-Sequence Distances, Image Processing On Line, 4 (2014), pp. 196–203. https://doi.org/10.5201/ipol.2014.68

Communicated by Bertrand Kerautret
Demo edited by Bertrand Kerautret

Abstract

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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