Title :
Stochastic analysis of scale-space smoothing
Author :
Åström, Kalle ; Heyden, Anders
Author_Institution :
Dept. of Math., Lund Univ., Sweden
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;
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-7282-X
DOI :
10.1109/ICPR.1996.546838
