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30 November 2001 Pattern recognition of images under linear and nonlinear transformations of intensity
Henri H. Arsenault, Daniel Lefebvre
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Proceedings Volume 10302, Optoelectronic Information Processing: Optics for Information Systems: A Critical Review; 103020D (2001) https://doi.org/10.1117/12.449675
Event: Optoelectronic Information Processing: Optics for Information Systems, 2002, Valencia, Spain
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.
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Henri H. Arsenault and Daniel Lefebvre "Pattern recognition of images under linear and nonlinear transformations of intensity", Proc. SPIE 10302, Optoelectronic Information Processing: Optics for Information Systems: A Critical Review, 103020D (30 November 2001); https://doi.org/10.1117/12.449675
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KEYWORDS
Pattern recognition
Sensors
Target recognition
Vector spaces
Yield improvement
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