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Proceedings Paper

Performance Of Synthetic Discriminant Functions For Infrared Ship Classification
Author(s): David Casasent; Vinod Sharma
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Paper Abstract

Our unified synthetic discriminant function (SDF) filter synthesis technique using the correlation matrix of the image training set is reviewed. Four different synthetic discriminant functions for intra-class recognition, inter-class discrimination and both intra and inter-class pattern recognition are considered. All techniques proposed are appropriate for object identification, location and classification in the presence of 3-D geometrical distortions in the input object. Initial results obtained on a set of four different classes of infrared ship imagery are presented. Excellent performance (over 90% correct classification) was achieved.

Paper Details

Date Published: 15 April 1983
PDF: 4 pages
Proc. SPIE 0422, 10th Intl Optical Computing Conf, (15 April 1983); doi: 10.1117/12.936152
Show Author Affiliations
David Casasent, Carnegie-Mellon University (United States)
Vinod Sharma, Carnegie-Mellon University (United States)


Published in SPIE Proceedings Vol. 0422:
10th Intl Optical Computing Conf
Sam Horvitz, Editor(s)

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