Open AccessThree-dimensional color object visualization and recognition using multi-wavelength computational holography
Author(s) -
Seokwon Yeom,
Bahram Javidi,
Pietro Ferraro,
Domenico Alfieri,
S. DeNicola,
Andrea Fińizio
Publication year - 2007
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.15.009394
Subject(s) - artificial intelligence , pattern recognition (psychology) , computer science , principal component analysis , visualization , digital holography , holography , computer vision , linear discriminant analysis , cognitive neuroscience of visual object recognition , object (grammar) , discriminant , process (computing) , optics , physics , operating system
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.