DocumentCode
3061594
Title
Chamfer masks: discrete distance functions, geometrical properties and optimization
Author
Thiel, Edouard ; Montanvert, Annick
Author_Institution
IMAG, Univ. Joseph Fourier, Grenoble, France
fYear
1992
fDate
30 Aug-3 Sep 1992
Firstpage
244
Lastpage
247
Abstract
The chamfer distances are based on the definition of masks whose size can change depending on the quality of the approximation which is expected, compared to the Euclidean distance. The authors show the induced geometrical properties of the generated distance images, and calculate the required properties of the mask to ensure that they define a distance function. Then they show how to optimize the masks directly in discrete space, and finally, present some main applications
Keywords
computational geometry; image processing; optimisation; Euclidean distance; chamfer distances; chamfer masks; discrete distance functions; distance images; image processing; induced geometrical properties; optimization; Aggregates; Application software; Cities and towns; Constraint theory; Euclidean distance; Extraterrestrial measurements; Image analysis; Image generation; Image sampling; Lattices;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 11th IAPR International Conference on
Conference_Location
The Hague
Print_ISBN
0-8186-2920-7
Type
conf
DOI
10.1109/ICPR.1992.201971
Filename
201971
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