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Related Concept Videos

Color Vision01:24

Color Vision

Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.
Ultraviolet and Visible (UV–Vis) Spectroscopy: Overview01:02

Ultraviolet and Visible (UV–Vis) Spectroscopy: Overview

Ultraviolet–visible (UV–visible or UV–Vis) spectroscopy is an analytical technique that investigates the interaction between matter and UV–Vis light within the electromagnetic spectrum. This method is widely used for its versatility, simplicity, and relatively quick data acquisition, making it valuable for both qualitative and quantitative analysis. When UV–Vis radiation passes through a material,  molecules absorb light depending on the energy required for electronic transitions. As a result...

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Related Experiment Video

Updated: Jun 22, 2026

Recording Ultra-Realistic Full-Color Analog Holograms for Use in a Moving Hologram Display
09:04

Recording Ultra-Realistic Full-Color Analog Holograms for Use in a Moving Hologram Display

Published on: January 14, 2020

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

Seokwon Yeom, Bahram Javidi, Pietro Ferraro

    Optics Express
    |June 24, 2009
    PubMed
    Summary
    This summary is machine-generated.

    Multi-wavelength digital holography enables 3D object recognition using color features. This technique efficiently classifies objects even with a limited number of training images.

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    Last Updated: Jun 22, 2026

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    Area of Science:

    • Optics and Photonics
    • Computer Vision
    • Pattern Recognition

    Background:

    • 3D object visualization and recognition are crucial in various fields.
    • Multi-wavelength digital holography offers a unique approach to capture 3D information.
    • Extracting detailed features like color from 3D objects remains a challenge.

    Purpose of the Study:

    • To develop and evaluate a method for 3D object visualization and recognition using multi-wavelength digital holography.
    • To leverage color features obtained from holographic reconstructions for improved object classification.
    • To assess the efficiency of statistical pattern recognition techniques in analyzing holographic data.

    Main Methods:

    • Utilizing multi-wavelength digital holography to acquire 3D object data.
    • Employing a perfect superimposition technique for consistent image reconstruction.
    • Applying statistical pattern recognition methods, including Principal Component Analysis (PCA) and Mixture Discriminant Analysis (MDA).
    • Estimating class-conditional probability density functions and using a maximum likelihood decision rule for classification.

    Main Results:

    • Successfully obtained multi-spectral color features from 3D objects using holography.
    • Reconstructed holographic images of consistent size through perfect superimposition.
    • Demonstrated the effectiveness of PCA and MDA in analyzing the spectral information.
    • Achieved accurate classification of unlabeled images into trained classes.

    Conclusions:

    • Multi-wavelength digital holography is a viable technique for 3D object visualization and recognition.
    • Color features extracted holographically significantly aid in object classification.
    • Statistical pattern recognition methods are effective for analyzing holographic spectral data.
    • A small dataset of training images is sufficient for robust color object classification.