IMAGE CLASSIFICATION BY AN OPTICAL IMPLEMENTATION OF THE FUKUNAGA-KOONTZ TRANSFORM.

James R. Leger, Sing H. Lee

Research output: Contribution to journalArticlepeer-review

42 Scopus citations

Abstract

The Fukunaga-Koontz (F-K) transform is a linear transformation that performs image-feature extraction for a two-class image classification problem. It has the property that the most important basis functions for representing one class of image data (in a least-squares sense) are also the least important for representing a second image class. A new method is presented of calculating the F-K basis functions for large dimensional imagery by using a small digital computer, when the intraclass variation can be approximated by correlation matrices of low rank. Having calculated the F-K basis functions, a coherent optical processor is used to obtain the coefficients of the F-K transform in parallel. Finally, these coefficients are detected electronically, and a classification is performed by the small digital computer.

Original languageEnglish (US)
Pages (from-to)556-564
Number of pages9
JournalJournal of the Optical Society of America
Volume72
Issue number5
DOIs
StatePublished - Jan 1 1982

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