Pruning of training sets used for synthetic discriminant function filter design by relaxing the correlation plane constraints

Bhagavatula Vijaya Kumar; Srinivas Bollapragada

doi:10.1117/12.169420

1 March 1994 Pruning of training sets used for synthetic discriminant function (SDF) filter design by relaxing the correlation plane constraints

Bhagavatula Vijaya Kumar, Srinivas Bollapragada

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Proceedings Volume 2237, Optical Pattern Recognition V; (1994) https://doi.org/10.1117/12.169420
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

Conventional synthetic discriminant function (SDF) filter designs use all available training images by requiring that the designed SDF filter yield prespecified values at the origin of the correlation plane when various training images are used in the input. In this paper, we show that we can reduce the number of training images being used and improve the filter performance by relaxing the correlation plane constraints when threshold detection is employed in the output correlation plane.

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Bhagavatula Vijaya Kumar and Srinivas Bollapragada "Pruning of training sets used for synthetic discriminant function (SDF) filter design by relaxing the correlation plane constraints", Proc. SPIE 2237, Optical Pattern Recognition V, (1 March 1994); https://doi.org/10.1117/12.169420

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KEYWORDS

Image filtering

Detection and tracking algorithms

Chemical elements

Optical pattern recognition

Missiles

Optical filters

Computer engineering

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