Stochastic Analysis of Scale-Space Smoothing

Åström, Karl; Heyden, Anders (1996). Stochastic Analysis of Scale-Space Smoothing 13th International Conference on Pattern Recognition, 2,, 305 - 309. 13th International Conference on Pattern Recognition, (ICPR 1996). Vienna, Austria: IEEE - Institute of Electrical and Electronics Engineers Inc.
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Conference Proceeding/Paper | Published | English
Authors:
Åström, Karl ; Heyden, Anders
Department:
Mathematics (Faculty of Engineering)
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
ISBN:
0 8186 7282 X
LUP-ID:
4c302050-491d-4fa3-a267-4299b6bad9d5 | Link: https://lup.lub.lu.se/record/4c302050-491d-4fa3-a267-4299b6bad9d5 | Statistics

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