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On the use of deformation matrices in artificial vision Systems*

Published online by Cambridge University Press:  09 March 2009

Guy Jumarie
Affiliation:
Department of Mathematics and Computer Sciences, Université du Québec à Montreal, P.O. Box 8888, St A, Montréal, Quebec H3C 3P8 (Canada)

Summary

At present, the procedure which is most widely used to identify an object consists of displacing its image in order that it be as close as possible to a reference pattern, and then to make a decision based upon the value of an Euclidean distance. This decision may be either in a deterministic framework or in a statistical one. The transformations so involved are translation and rotation. It is shown that, if one takes for granted the invariance of the amount of information involved by the object considered as an informational source, then there is another class of transformations, referred to as deformation, which should be also taken into account. The question is examined, and its consequences in the design of artificial vision are outlined in both the deterministic and stochastic cases.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1988

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References

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