Color accessibility in JavaScript (video tutorial)

Overview

This video tutorial shows you how to analyze your images for color accessibility, and apply transformations both to simulate how color blind people may experience your images, and to assist them to distinguish similar-looking colors.

Video tutorial

Tutorial contents

This tutorial presents the following topics. Click a timestamp to jump to that part of the video.

Introduction

0:00	Cloudinary can help you to see your images through the eyes of a color blind person, both subjectively and objectively, and provides transformations to make them more accessible.

Why you should care about color accessibility

0:19	One in twelve men, and one in two hundred women suffer from Color Vision Deficiency. That's a significant proportion of the population who may miss vital information or are unable to engage fully with your site. Cloudinary allows you to experience all the different types of color blindness, by applying simple transformations.

How to simulate color blindness

0:47	In a JavaScript environment, install and configure the Cloudinary JavaScript SDK for your product environment, import the simulateColorBlind effect, and apply the effect your image. Here, publicId and colorType are both strings defined elsewhere in the app (see the full list of conditions in the Transformation URL API Reference):

How to assist with color blindness

1:16	You can apply stripes or an X-ray effect to images to help color blind people to distinguish one color from another. Import assistColorBlind and apply either the xray() or stripesStrength() version of the effect to your image. For stripes, specify the strength of the stripes from 1 to 100:

Analyze your images objectively

1:59	The Accessibility analysis feature lets you analyze your images objectively, to determine which of your images may cause problems for color blind people. Set the accessibility_analysis option to true when uploading images to return a color blind accessibility score, together with an analysis of the issues and the colors that may be the most problematic. See an example in this GitHub repo.

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