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Stochastic Analysis of Scale-Space Smoothing

Åström, Karl LU and Heyden, Anders LU (1996) 13th International Conference on Pattern Recognition, (ICPR 1996) In 13th International Conference on Pattern Recognition 2. p.305-309
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
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
computer vision, correlation methods, feature extraction, interpolation, smoothing methods, stochastic processes
in
13th International Conference on Pattern Recognition
volume
2
pages
305 - 309
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
13th International Conference on Pattern Recognition, (ICPR 1996)
external identifiers
  • Scopus:84898833093
ISBN
0 8186 7282 X
DOI
10.1109/ICPR.1996.546838
language
English
LU publication?
yes
id
4c302050-491d-4fa3-a267-4299b6bad9d5 (old id 787192)
alternative location
http://ieeexplore.ieee.org/iel3/3995/11503/00546838.pdf?tp=&arnumber=546838&isnumber=11503
date added to LUP
2008-03-31 13:53:13
date last changed
2016-10-13 04:40:49
@misc{4c302050-491d-4fa3-a267-4299b6bad9d5,
  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},
  author       = {Åström, Karl and Heyden, Anders},
  isbn         = {0 8186 7282 X},
  keyword      = {computer vision,correlation methods,feature extraction,interpolation,smoothing methods,stochastic processes},
  language     = {eng},
  pages        = {305--309},
  publisher    = {ARRAY(0xa4147e0)},
  series       = {13th International Conference on Pattern Recognition},
  title        = {Stochastic Analysis of Scale-Space Smoothing},
  url          = {http://dx.doi.org/10.1109/ICPR.1996.546838},
  volume       = {2},
  year         = {1996},
}