DocumentCode
2403369
Title
Stochastic analysis of scale-space smoothing
Author
Åström, Kalle ; Heyden, Anders
Author_Institution
Dept. of Math., Lund Univ., Sweden
Volume
2
fYear
1996
fDate
25-29 Aug 1996
Firstpage
305
Abstract
In the high-level operations of computer vision it is taken for granted that image features have been reliably detected. This paper addresses the problem of feature extraction by scale-space methods. This paper is based on two key ideas: to investigate the stochastic properties of scale-space representations, and to investigate the interplay between discrete and continuous images. These investigations are then used to predict the stochastic properties of sub-pixel feature detectors
Keywords
computer vision; correlation methods; feature extraction; interpolation; smoothing methods; stochastic processes; computer vision; continuous images; correlation; discrete images; feature extraction; image acquisition; image features; interpolation; scale-space smoothing; stochastic analysis; sub-pixel feature detectors; Cameras; Computer vision; Geometrical optics; Image edge detection; Image sampling; Interpolation; Kernel; Optical noise; Smoothing methods; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location
Vienna
ISSN
1051-4651
Print_ISBN
0-8186-7282-X
Type
conf
DOI
10.1109/ICPR.1996.546838
Filename
546838
Link To Document