Anti-aliased Euclidean distance transform

Authors:
Stefan Gustavson;Robin Strand
Affiliations:
Media and Information Technology, Linköping University, Sweden;Centre for Image Analysis, Uppsala University, Sweden
Venue:
Pattern Recognition Letters
Year:
2011

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Abstract

We present a modified distance measure for use with distance transforms of anti-aliased, area sampled grayscale images of arbitrary binary contours. The modified measure can be used in any vector-propagation Euclidean distance transform. Our test implementation in the traditional SSED8 algorithm shows a considerable improvement in accuracy and homogeneity of the distance field compared to a traditional binary image transform. At the expense of a 10x slowdown for a particular image resolution, we achieve an accuracy comparable to a binary transform on a supersampled image with 16x16 higher resolution, which would require 256 times more computations and memory.