Title :
Learning visual operators from examples: a new paradigm in image processing
Author :
Knutsson, Hans ; Borga, M.
Author_Institution :
Comput. Vision Lab., Linkoping Univ., Sweden
Abstract :
This paper presents a general strategy for designing efficient visual operators. The approach is highly task-oriented and what constitutes the relevant information is defined by a set of examples. The examples are pairs of images displaying a strong dependence in the chosen feature but are otherwise independent. Particularly important concepts in the work are mutual information and canonical correlation. Visual operators learned from examples are presented, e.g., local shift-invariant orientation operators and image content-invariant disparity operators. Interesting similarities to biological vision functions are observed
Keywords :
correlation methods; feature extraction; image processing; learning by example; mathematical operators; canonical correlation; feature dependence; image content-invariant disparity; image pairs; image processing; learning from examples; local shift-invariant orientation; mutual information; task-oriented approach; visual operators; Computer vision; Control theory; Data mining; Ear; Image analysis; Image processing; Laboratories; Learning systems; Mutual information; Read only memory;
Conference_Titel :
Image Analysis and Processing, 1999. Proceedings. International Conference on
Conference_Location :
Venice
Print_ISBN :
0-7695-0040-4
DOI :
10.1109/ICIAP.1999.797571
