I am wanting to create a function that would determine how colorblind-friendly an image is (on a scale from 0-1). I have several color-related functions that are capable of performing the following tasks:
Take an image (as a PIL image, filename, or RGB array) and transform it into an image representative of what a colorblind person would see (for the different types of colorblindness)
Take an image and determine the rgb colors associated with each pixel of the image (transform into numpy array of rgb colors)
Determine the color palette associated with an image
Find the similarity between two rgb arrays (using CIELAB- see colormath package)
My first instinct was to transform the image and colorblind version of the image into RGB arrays and then use the CIELAB function to determine the similarity between the two images. However, that doesn't really solve the problem since it wouldn't be able to pick out things like readability (e.g. if the text and background color end up being very similar after adjusting for colorblindness).
Any ideas for how to determine how colorblind-friendly an image is?