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
Link To Document :
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