title: Three-dimensional color object visualization and recognition using multi-wavelength computational holography.
abstract: 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.
authors: Seokwon
authors: S
authors: Yeom
authors: Bahram
authors: B
authors: Javidi
authors: Pietro
authors: P
authors: Ferraro
authors: Domenico
authors: D
authors: Alfieri
authors: Sergio
authors: S
authors: Denicola
authors: Andrea
authors: A
authors: Finizio