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Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Vol. 11, Iss. 5 — May. 1, 1994
  • pp: 1610–1618

Recognition of rotated images by invariant Karhunen–Loeve expansion

Ran Hilai and Jacob Rubinstein  »View Author Affiliations


JOSA A, Vol. 11, Issue 5, pp. 1610-1618 (1994)
http://dx.doi.org/10.1364/JOSAA.11.001610


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Abstract

Given an ensemble of images, we consider a method for the extraction of optimal features that are invariant under two-dimensional rotations. Our method consists of first identifying some characteristics of the optimal basis functions and then applying the Karhunen–Loeve algorithm to determine them completely. We perform a few classification experiments with the invariant features, using a neural network as a classifier. The new method is compared with the Zernike moments method.

© 1994 Optical Society of America

History
Original Manuscript: August 13, 1993
Revised Manuscript: October 29, 1993
Manuscript Accepted: November 8, 1993
Published: May 1, 1994

Citation
Ran Hilai and Jacob Rubinstein, "Recognition of rotated images by invariant Karhunen–Loeve expansion," J. Opt. Soc. Am. A 11, 1610-1618 (1994)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-11-5-1610

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