DocumentCode :
3311413
Title :
Scale-space from nonlinear filters
Author :
Bangham, Andrew J. ; Ling, Paul ; Harvey, Richard
Author_Institution :
Sch. of Inf. Syst., East Anglia Univ., Norwich, UK
fYear :
1995
fDate :
20-23 Jun 1995
Firstpage :
163
Lastpage :
168
Abstract :
Decomposition by extrema is put into the context of linear vision systems and scale-space. One dimensional discrete M- and N-sieves neither introduce new edges as the scale increases nor create new extrema. They share this property with diffusion based filters. Furthermore M- and N-sieve algorithms are extremely fast with order complexity n. Used to decompose an image, the resulting granularity is appropriate for pattern recognition
Keywords :
computational complexity; computer vision; image recognition; nonlinear filters; 1D discrete M-sieves; 1D discrete N-sieves; diffusion based filters; extrema decomposition; granularity; image decomposition; linear vision systems; nonlinear filters; order complexity; pattern recognition; scale-space; Convolution; Image analysis; Image processing; Image recognition; Information systems; Layout; Machine vision; Nonlinear filters; Signal analysis; Smoothing methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 1995. Proceedings., Fifth International Conference on
Conference_Location :
Cambridge, MA
Print_ISBN :
0-8186-7042-8
Type :
conf
DOI :
10.1109/ICCV.1995.466791
Filename :
466791
Link To Document :
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