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Proceedings Paper

Pattern recognition of images under linear and nonlinear transformations of intensity
Author(s): Henri H. Arsenault; Daniel Lefebvre
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Paper Abstract

We review correlation methods for pattern recognition that are invariant to a transformation af(x,y)+b of unsegmented targets. This linear transformation is an approximation to nonlinear image transformations such as those caused by detector nonlinearities. The case b=O corresponds to a change of illumination of the object with respect to the reference. Earlier methods had considered only the latter case; here we introduce a technique for the more general case. We show that two of the invariant methods are equivalent to measuring the angles between the reference and the targets in a multidimensional vector space. Experimental results that compare the various methods with and without noise show that the new method yields results that are much improved over the previous methods.

Paper Details

Date Published: 30 November 2001
PDF: 24 pages
Proc. SPIE 10302, Optoelectronic Information Processing: Optics for Information Systems: A Critical Review, 103020D (30 November 2001); doi: 10.1117/12.449675
Show Author Affiliations
Henri H. Arsenault, COPL Institute, Univ. Laval (Canada)
Daniel Lefebvre, COPL Institute, Univ. Laval (Canada)

Published in SPIE Proceedings Vol. 10302:
Optoelectronic Information Processing: Optics for Information Systems: A Critical Review
Philippe Refregier; Bahram Javidi; Carlos Ferreira; Santiago Vallmitjana, Editor(s)

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