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A Linear Euclidean Distance Transform Algorithm Based on the Linear-Time Legendre Transform
The University of Victoria, Victoria, British Columbia, Canada May 09-May 11
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CRV.2005.7The 2nd Canadian Conference on Comput ...
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Yves Lucet, "A Linear Euclidean Distance Transform Algorithm Based on the Linear-Time Legendre Transform," Computer and Robot Vision, Canadian Conference, pp. 262-267, The 2nd Canadian Conference on Computer and Robot Vision (CRV'05), 2005.
 
 
BibTex
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@article{ 10.1109/CRV.2005.7,
author = {Yves Lucet},
title = {A Linear Euclidean Distance Transform Algorithm Based on the Linear-Time Legendre Transform},
journal ={Computer and Robot Vision, Canadian Conference},
volume = {0},
year = {2005},
isbn = {0-7695-2319-6},
pages = {262-267},
doi = {http://doi.ieeecomputersociety.org/10.1109/CRV.2005.7},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Computer and Robot Vision, Canadian Conference
TI - A Linear Euclidean Distance Transform Algorithm Based on the Linear-Time Legendre Transform
SN - 0-7695-2319-6
SP262
EP267
A1 - Yves Lucet,
PY - 2005
KW - null
VL - 0
JA - Computer and Robot Vision, Canadian Conference
ER -
 
Yves Lucet, University of British Columbia - Okanagan Campus, Okanagan University College, Canada
We introduce a new exact Euclidean distance transform algorithm for binary images based on the Linear-time Legendre Transform algorithm. The three-step algorithm uses dimension reduction and convex analysis results on the Legendre-Fenchel transform to achieve linear-time complexity. First, computation on a grid (the image) is reduced to computation on a line, then the convex envelope is computed, and finally the squared Euclidean distance transform is obtained. Examples and an extension to non-binary images are provided.
Citation:
Yves Lucet, "A Linear Euclidean Distance Transform Algorithm Based on the Linear-Time Legendre Transform," crv, pp.262-267, The 2nd Canadian Conference on Computer and Robot Vision (CRV'05), 2005
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