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Color Theory in Computer Vision

Color Theory in Computer Vision

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.

Photo by Paweł Czerwiński on Unsplash

Color Vision

Source

History of Color theory:

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

Source

RYB colors

Proof as to why RYB was Considered to be primary colors

Source

Trichromatic Theory

Three types of cone photoreceptors

Source

RGB Space Spanning

Source

Opponent color theory

Gray Scale

Use cases

RGB

Source

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

Convert RGB to YCrCb using SkImage

CIE-XYZ

Source

Convert RGB to XYZ using SkImage

HSV

Source

Convert RGB to HSV using Skimage

Other Color Spaces

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

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