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Anti-aliased Euclidean distance transform
Department of Science and Technology, Linköping University. (Media and Information Technology)
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
2011 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 32, no 2, 252-257 p.Article in journal (Refereed) Published
Abstract [en]

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 10× slowdown for a particular image resolution, we achieve an accuracy comparable to a binary transform on a supersampled image with 16 × 16 higher resolution, which would require 256 times more computations and memory.

Place, publisher, year, edition, pages
2011. Vol. 32, no 2, 252-257 p.
Keyword [en]
Distance transform, Vector propagation, Euclidean metric, Sub-pixel accuracy
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-133946DOI: 10.1016/j.patrec.2010.08.010ISI: 000285703800019OAI: oai:DiVA.org:uu-133946DiVA: diva2:371155
Available from: 2010-11-19 Created: 2010-11-19 Last updated: 2017-12-12Bibliographically approved

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Strand, Robin

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