DocumentCode :
2473028
Title :
Force histograms computed in O(NlogN)
Author :
Ni, JingBo ; Matsakis, Pascal
Author_Institution :
Univ. of Guelph, Guelph, ON, Canada
fYear :
2008
fDate :
8-11 Dec. 2008
Firstpage :
1
Lastpage :
4
Abstract :
The relative position between two objects in a 2D raster image is often represented quantitatively by a force histogram. In the general case, force histograms are computed in O(KN¿N) time: N is the number of pixels in the image and K is the number of directions in which forces are considered. When the objects are defined as fuzzy sets, this complexity also depends quadratically on the number M of possible membership degrees. In the present paper, an algorithm that runs in O(NlogN) is introduced. Computation times are basically independent of K and M. All objects (convex, concave, crisp, fuzzy) are handled in an equally fast manner. Experiments validate the theoretical analysis.
Keywords :
computational complexity; fuzzy set theory; image representation; 2D raster image; force histograms; fuzzy sets; Biomedical imaging; Cranium; Fast Fourier transforms; Fuzzy sets; Geographic Information Systems; Histograms; Image databases; Indexing; Layout; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
ISSN :
1051-4651
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
Type :
conf
DOI :
10.1109/ICPR.2008.4761010
Filename :
4761010
Link To Document :
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