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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 15, Iss. 15 — Jul. 23, 2007
  • pp: 9394–9402

Three-dimensional color object visualization and recognition using multi-wavelength computational holography

Seokwon Yeom, Bahram Javidi, Pietro Ferraro, Domenico Alfieri, Sergio DeNicola, and Andrea Finizio  »View Author Affiliations

Optics Express, Vol. 15, Issue 15, pp. 9394-9402 (2007)

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In this paper, we address 3D object visualization and recognition with multi-wavelength digital holography. Color features of 3D objects are obtained by the multiple-wavelengths. Perfect superimposition technique generates reconstructed images of the same size. Statistical pattern recognition techniques: principal component analysis and mixture discriminant analysis analyze multi-spectral information in the reconstructed images. Class-conditional probability density functions are estimated during the training process. Maximum likelihood decision rule categorizes unlabeled images into one of trained-classes. It is shown that a small number of training images is sufficient for the color object classification.

© 2007 Optical Society of America

OCIS Codes
(000.5490) General : Probability theory, stochastic processes, and statistics
(090.0090) Holography : Holography
(090.1760) Holography : Computer holography
(100.5010) Image processing : Pattern recognition
(100.6890) Image processing : Three-dimensional image processing

ToC Category:

Original Manuscript: April 17, 2007
Revised Manuscript: June 20, 2007
Manuscript Accepted: June 21, 2007
Published: July 16, 2007

Seokwon Yeom, Bahram Javidi, Pietro Ferraro, Domenico Alfieri, Sergio DeNicola, and Andrea Finizio, "Three-dimensional color object visualization and recognition using multi-wavelength computational holography," Opt. Express 15, 9394-9402 (2007)

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