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An Efficient Euclidean Distance Transform

  • Donald G Bailey
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3322)

Abstract

Within image analysis the distance transform has many applications. The distance transform measures the distance of each object point from the nearest boundary. For ease of computation, a commonly used approximate algorithm is the chamfer distance transform. This paper presents an efficient linear- time algorithm for calculating the true Euclidean distance-squared of each point from the nearest boundary. It works by performing a 1D distance transform on each row of the image, and then combines the results in each column. It is shown that the Euclidean distance squared transform requires fewer computations than the commonly used 5x5 chamfer transform.

Keywords

Voronoi Diagram Lookup Table Background Pixel City Block Current Pixel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Donald G Bailey
    • 1
  1. 1.Institute of Information Sciences and TechnologyMassey UniversityPalmerston NorthNew Zealand

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