DocumentCode
798434
Title
Linear time Euclidean distance transform algorithms
Author
Breu, Heinz ; Gil, Joseph ; Kirkpatrick, David ; Werman, Michael
Author_Institution
Dept. of Comput. Sci., British Columbia Univ., Vancouver, BC, Canada
Volume
17
Issue
5
fYear
1995
fDate
5/1/1995 12:00:00 AM
Firstpage
529
Lastpage
533
Abstract
Two linear time (and hence asymptotically optimal) algorithms for computing the Euclidean distance transform of a two-dimensional binary image are presented. The algorithms are based on the construction and regular sampling of the Voronoi diagram whose sites consist of the unit (feature) pixels in the image. The first algorithm, which is of primarily theoretical interest, constructs the complete Voronoi diagram. The second, more practical, algorithm constructs the Voronoi diagram where it intersects the horizontal lines passing through the image pixel centers. Extensions to higher dimensional images and to other distance functions are also discussed
Keywords
computational geometry; image processing; transforms; Voronoi diagram; asymptotically optimal algorithms; linear time Euclidean distance transform algorithms; regular sampling; two-dimensional binary image; Computer vision; Councils; Euclidean distance; Histograms; Image databases; Indexing; Layout; Lighting; Object recognition; Optimized production technology;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.391389
Filename
391389
Link To Document