Color Ambiguity Scoring for Accessibility
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Solution Overview
Problem
Electronic devices and communication systems often create and disseminate color content that is difficult for individuals with color vision deficiency to understand, as they lack awareness of color ambiguity issues affecting color-blind users.
Innovation Solution
A system that generates color ambiguity scores to quantify the difficulty of color content for users with color vision deficiency, incorporating a color ambiguity score generator to analyze images and videos, and performs mitigation operations such as alert notifications, image editing, or content replacement to reduce ambiguity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If color content is created and disseminated without awareness of color ambiguity, then the content can be produced efficiently and quickly, but the content becomes difficult for individuals with color vision deficiency to understand
Solution Approach 1:
The system performs preliminary analysis of color content to generate ambiguity scores before the content is fully disseminated. By calculating local and global color ambiguity scores in advance, the system enables content creators to identify and correct accessibility issues prior to final publication, thus maintaining production efficiency while improving color accessibility.
Solution Approach 2:
The system provides feedback through generated ambiguity scores that indicate the level of color ambiguity in the content. This feedback mechanism allows content creators to adjust their work to improve accessibility while maintaining efficient production workflows, as the automated scoring eliminates the need for manual color accessibility evaluation.
2Reliability
If color ambiguity analysis and mitigation operations are performed, then accessibility for color-blind users is enhanced, but the processing time and computational resources increase
Solution Approach 1:
The analysis is divided into separate local and global color ambiguity score calculations. The local score evaluates individual objects within the image, while the global score assesses the overall color relationships. This segmentation allows for optimized processing where only relevant portions of the content require intensive analysis, reducing total processing time while maintaining comprehensive accessibility evaluation.
3Loss of information
If automated color ambiguity scoring is implemented, then awareness of color ambiguity issues is improved, but the system complexity increases
Solution Approach 1:
The system automatically generates color ambiguity scores and identifies problematic color combinations without requiring manual intervention or expert knowledge. The automated scoring mechanism serves the system itself by providing the information needed to make accessibility improvements, eliminating the need for complex manual evaluation processes while maintaining high awareness of color ambiguity issues.
Data Source
AI summary
Systems, devices, and methods for determining color ambiguity of images or videos. A system includes a color ambiguity score generator, which analyzes an image and determines a color ambiguity score that quantitively indicates a level of color ambiguity that the image is estimated to cause when viewed by a user having color vision deficiency. A local color ambiguity score is generated to quantitively indicate a level of local color ambiguity between (i) an in-image object and (ii) an in-image foreground of that in-image object. A global color ambiguity score is generated to quantitively indicate a level of global color ambiguity between (I) a first in-image object within the image and (II) a second in-image object within that image. The color ambiguity score generator generates the color ambiguity score by utilizing a formula that uses both (A) the local color ambiguity score and (B) the global color ambiguity score.