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Performance measures for correlation filters

Applied Optics, 1990
Several performance criteria are described to enable a fair comparison among the various correlation filter designs: signal-to-noise ratio, peak sharpness, peak location, light efficiency, discriminability, and distortion invariance. The trade-offs resulting between some of these criteria are illustrated with the help of a new family of filters called ...
B V, Kumar, L, Hassebrook
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Biometric verification with correlation filters

Applied Optics, 2004
Using biometrics for subject verification can significantly improve security over that of approaches based on passwords and personal identification numbers, both of which people tend to lose or forget. In biometric verification the system tries to match an input biometric (such as a fingerprint, face image, or iris image) to a stored biometric template.
B V K, Vijaya Kumar   +5 more
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CROSS‐CORRELATION FILTERING

GEOPHYSICS, 1954
Correlation analysis techniques may be applied to seismic data already subjected to standard recording and analysis procedure in an effort to extract additional information, or to raw data as an alternative filtering method. These techniques involve determination of certain parameters which provide a quantitative measure of the correlation between two
Hal J. Jones, John A. Morrison
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Minimum average correlation energy filters

Applied Optics, 1987
The synthesis of a new category of spatial filters that produces sharp output correlation peaks with controlled peak values is considered. The sharp nature of the correlation peak is the major feature emphasized, since it facilitates target detection.
A, Mahalanobis, B V, Kumar, D, Casasent
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Quadratic correlation filters for optical correlators

SPIE Proceedings, 2003
Linear correlation filters have been implemented in optical correlators and successfully used for a variety of applications. The output of an optical correlator is usually sensed using a square law device (such as a CCD array) which forces the output to be the squared magnitude of the desired correlation.
Abhijit Mahalanobis   +2 more
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Minimum noise and correlation energy optical correlation filter

Applied Optics, 1992
A new distortion-invariant optical correlation filter to produce easily detectable correlation peaks in the presence of noise and clutter and to provide better intraclass recognition is presented. The basic ideas of the minimum variance synthetic discriminant function correlation filter (which minimizes noise variance in the output correlation peak ...
G, Ravichandran, D, Casasent
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Rotationally invariant correlation filtering

Journal of the Optical Society of America A, 1985
A method is presented for analyzing and designing optical correlation filters that have tailored rotational invariance properties. The concept of a correlation of an image with a rotation of itself is introduced. A unified theory of rotation-invariant filtering is then formulated.
George F. Schils, Donald W. Sweeney
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Purely real correlation filters

SPIE Proceedings, 1991
A general algorithm for synthesizing purely real correlation filters in the frequency domain is developed using the method of Lagrange multipliers. This method can be applied to filters which can be derived using linearly constrained quadratic minimization.
Abhijit Mahalanobis, Sewoong Song
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Distortion tolerant correlation filter design

Applied Optics, 2013
This paper introduces a computationally efficient algorithm for synthesis of a distortion tolerant correlation filter and associated threshold, denoted collectively as the enhanced matched filter (EMF). Application areas of EMF include imagery based automatic target detection and recognition and biometrics. The EMF is synthesized from a set of training
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Generalized linear correlation filters

SPIE Proceedings, 2013
We present two generalized linear correlation filters (CFs) that encompass most of the state-of-the-art linear CFs. The common criteria that arc used in linear CF design are the mean squared error (MSE), output noise variance (ONV), and average similarity measure (ASM).
Andres Rodriguez, B. V. K. Vijaya Kumar
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