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Optical Engineering

General methodology for simultaneous representation and discrimination of multiple object classes
Author(s): Ashit Talukder; David P. Casasent
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Paper Abstract

We address a new general method for linear and nonlinear feature extraction for simultaneous representation and classification. We call this approach the maximum representation and discrimination feature (MRDF) method. We develop a novel nonlinear eigenfeature (NLEF) extraction technique to represent data with closed-form solutions and use it to derive a nonlinear MRDF algorithm. Results of the MRDF method on synthetic databases are shown and compared with results from standard Fukunaga-Koontz transform and Fisher discriminant function methods. The method is also applied to an automated product inspection problem (discrimination) and for classification and pose estimation of two similar objects under 3-D aspect angle variations (representation and discrimination).

Paper Details

Date Published: 1 March 1998
PDF: 10 pages
Opt. Eng. 37(3) doi: 10.1117/1.601925
Published in: Optical Engineering Volume 37, Issue 3
Show Author Affiliations
Ashit Talukder, Carnegie Mellon Univ. (United States)
David P. Casasent, Carnegie Mellon Univ. (United States)

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