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Proceedings Paper

Decision regions of Fourier plane nonlinear filtering for image recognition
Author(s): Bahram Javidi; Nasser Towghi; Jian Li
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Paper Abstract

In image recognition applications, complex decision regions in the image space are needed. Linear filtering forms the decision regions by hyperplanes in the image space. We determine the decision region formed by Fourier plane nonlinear filtering. In the case that power law nonlinearity is applied in the Fourier plane, the decision region turns out to be approximately an n-dimensional parabola which opens toward the direction of the reference vector. That is, the intersection of the decision region with any plan (two dimensional vector space) not containing any vector parallel to the reference vector, is a bounded convex region enclosed by a closed curve. The size of the convex region depends on the filter nonlinearity, which determines the distortion robustness and discrimination capability of the filter. It can be adjusted by choosing different Fourier plane nonlinearities and/or different threshold values at the output plane. These types of regions are desirable and well suited in image recognition.

Paper Details

Date Published: 9 October 1998
PDF: 15 pages
Proc. SPIE 3466, Algorithms, Devices, and Systems for Optical Information Processing II, (9 October 1998); doi: 10.1117/12.326797
Show Author Affiliations
Bahram Javidi, Univ. of Connecticut (United States)
Nasser Towghi, Univ. of Connecticut (United States)
Jian Li, SUNY/Stony Brook (United States)


Published in SPIE Proceedings Vol. 3466:
Algorithms, Devices, and Systems for Optical Information Processing II
Bahram Javidi; Demetri Psaltis, Editor(s)

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