Color Theory in Computer Vision

Last Updated on January 6, 2023 by Editorial Team

Author(s): Akula Hemanth Kumar

Computer Vision

Making computer vision easy with Monk, a low code Deep Learning tool, and a unified wrapper for Computer Vision.

Color Vision

History of Color theory:

Color model from the book “Theory of Colors” by Johann Wolfgang.

RYB colors

Proof as to why RYB was Considered to be primary colors

Trichromatic Theory

• Also known as Young-Helmholtz theory.

Three types of cone photoreceptors

• Short-preferring(Blue)
• Middle-preferring(Green)
• Long-preferring(Red)

RGB Space Spanning

Opponent color theory

• There are colors not directly perceivable in normal lighting conditions.
• The trichromatic theory fails to incorporate these colors.
• The opponent-process works through excitatory and inhibitory responses, with the two components of each mechanism opposing each other.

Gray Scale

• Monochromatic Single Channel
• Pixel values from 0(Black) to 255(White)
• Grayscale images contain only shades of gray.

Use cases

• Less data complexity and storage requirements
• Many applications work well with gray scales. Complex channels are not required.
• Improved computation speeds.

RGB

• The additive color space is based on the RGB color model.
• Three Channels Red, Green, and Blue.
• Used in many image processing and computer vision applications.

Accessing channels of RGB image using OpenCV

Additive and Subtractive Color Theory

Convert RGB to CMYK using PIL

CIE -LAB

L -Lightness ( Intensity)

a -Green to Magenta

b -Blue to Yellow

Convert RGB to LAB using SkImage

CIE-YCrCb

Y-Luminance , Cr -Red, Cb -Blue

• Resemblance with YUV mode

Convert RGB to YCrCb using SkImage

CIE-XYZ

Convert RGB to XYZ using SkImage

HSV

Convert RGB to HSV using Skimage

Other Color Spaces

• Haematoxylin-Eosin-DAB(HED)
• CIE-LCH color space
• YUV color space
• YIQ color space
• Stain color space
• HSL color space

You can find the complete jupyter notebook here.

If you have any questions, you can reach Abhishek. Feel free to reach out to him.

I am extremely passionate about computer vision and deep learning. I am an open-source contributor to Monk Libraries.

You can also see my other writings at:

Akula Hemanth Kumar – Medium

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Published via Towards AI