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Related Concept Videos

Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
Different compounds display unique properties due to their...
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the C=O, C=N, and C=C occur between 1600–1850 cm−1.
The...
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.
Photoreceptors and Visual Pathways01:22

Photoreceptors and Visual Pathways

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Perceptual Constancy01:12

Perceptual Constancy

Perceptual constancy is the ability to recognize that objects remain consistent and unchanged even when their appearance varies due to changes in sensory input. There are four main types of perceptual constancy: size constancy, shape constancy, color constancy, and brightness constancy.
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IR Spectrum01:19

IR Spectrum

When infrared (IR) radiation passes through a molecule, the bonds stretch or bend by absorbing the radiation. This absorption creates the molecule's absorption spectrum, which is the plot of its percentage transmittance versus wavenumber.
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Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores
09:46

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Published on: August 19, 2013

Chromaticity space for illuminant invariant recognition.

Sivalogeswaran Ratnasingam, T Martin McGinnity

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |April 7, 2012
    PubMed
    Summary
    This summary is machine-generated.

    A new algorithm extracts illuminant invariant chromaticity features for robust machine vision. This method enhances color object recognition and skin detection across diverse lighting conditions and imaging devices.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Color Science

    Background:

    • Color constancy is crucial for reliable machine vision.
    • Existing algorithms struggle with non-uniform illumination and unknown camera sensitivities.
    • Accurate color analysis is essential for object recognition and scene understanding.

    Purpose of the Study:

    • To develop an algorithm for extracting illuminant invariant chromaticity features.
    • To enable robust color-based object recognition and skin detection under varying illuminants.
    • To provide a method compatible with cameras of unknown sensitivity.

    Main Methods:

    • Pixel-level extraction of two chromaticity features from image sensor responses.
    • Testing algorithm performance with standard and indoor illuminants.
    • Evaluating skin detection accuracy across diverse lighting and ethnic backgrounds.

    Main Results:

    • The algorithm demonstrated good performance in separating perceptually similar colors.
    • Achieved superior color-based object recognition compared to existing methods.
    • Outperformed standard color spaces in illuminant-invariant skin detection.

    Conclusions:

    • The proposed illuminant invariant chromaticity space is effective for machine vision.
    • Enables robust object recognition and skin detection independent of illumination.
    • Offers a valuable tool for applications requiring consistent color analysis.