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Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Editor: Stephen A. Burns
  • Vol. 24, Iss. 11 — Nov. 1, 2007
  • pp: 3403–3417

Design of correlation filters for recognition of linearly distorted objects in linearly degraded scenes

Erika M. Ramos-Michel and Vitaly Kober  »View Author Affiliations

JOSA A, Vol. 24, Issue 11, pp. 3403-3417 (2007)

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Generalized correlation filters are proposed to improve recognition of a linearly distorted object embedded in a nonoverlapping background when the input scene is degraded with a linear system and additive noise. Several performance criteria defined for the nonoverlapping signal model are used for the design of filters. The derived filters take into account information about an object to be recognized, disjoint background, noise, and linear degradations of the target and the input scene. Computer simulation results obtained with the proposed filters are discussed and compared with those of various correlation filters in terms of discrimination capability, location errors, and tolerance to input noise.

© 2007 Optical Society of America

OCIS Codes
(100.2000) Image processing : Digital image processing
(100.5010) Image processing : Pattern recognition

ToC Category:
Image Processing

Original Manuscript: April 9, 2007
Revised Manuscript: August 6, 2007
Manuscript Accepted: August 14, 2007
Published: October 1, 2007

Erika M. Ramos-Michel and Vitaly Kober, "Design of correlation filters for recognition of linearly distorted objects in linearly degraded scenes," J. Opt. Soc. Am. A 24, 3403-3417 (2007)

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