Content Editing System for Target Contrast Ratio Modification
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Solution Overview
Problem
Conventional systems for selecting colors that meet target contrast ratios for web content accessibility are cumbersome and prone to errors, requiring extensive manual interaction and trial-and-error due to limited control over relative luminance values.
Innovation Solution
A content editing system that allows users to select a color set, convert it into a different color space (e.g., CIE 1931 xyY), and manipulate luminance values to generate candidate color sets with improved contrast ratios, enabling precise control over contrast values and reducing manual effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional color selection systems are used, then users can select colors with basic controls, but the process requires extensive manual interaction and trial-and-error to achieve target contrast ratios
Solution Approach 1:
The system transforms color selection from traditional hue/saturation/brightness parameters to relative luminance values as the primary control parameter. This allows direct manipulation of the parameter that determines contrast ratio, enabling precise control over contrast while simplifying the operation. Users can now directly adjust luminance values to achieve target contrast ratios without iterative trial-and-error.
Solution Approach 2:
The system introduces an automated computation intermediary that calculates the relationship between foreground and background luminance values. This intermediary automatically determines whether selected colors meet target contrast ratios and provides guidance for adjustment, eliminating the need for manual trial-and-error while maintaining ease of operation.
2Reliability
If conventional color selection systems are used, then users can navigate color gamut with limited controls, but the process is cumbersome and prone to errors
Solution Approach 1:
The system changes the control parameter from indirect color attributes to direct relative luminance values. This parameter change ensures that color selections automatically adhere to contrast requirements, improving reliability while the simplified luminance-based interface actually reduces perceived complexity for users.
Solution Approach 2:
The system provides real-time feedback on whether selected color combinations meet target contrast ratios. This feedback mechanism guides users toward accurate color selections without requiring them to understand complex contrast calculations, thereby improving reliability while maintaining user-friendly operation.
3Productivity
If manual trial-and-error method is used, then users can eventually find colors that meet contrast ratios, but the process requires extensive manual interaction and time
Solution Approach 1:
The system replaces the manual mechanical trial-and-error process with automated computational evaluation. The system instantly calculates contrast ratios for selected colors and provides direct feedback, eliminating the need for repeated manual adjustments and significantly improving productivity while reducing time investment.
Solution Approach 2:
An automated computation intermediary performs the contrast ratio calculations and evaluation that previously required manual trial-and-error. This intermediary provides instant feedback on whether colors meet requirements, dramatically reducing the time needed for color selection while maintaining high productivity.
4Measurement precision
If conventional color systems are used, then users can select colors with limited controls, but each control affects relative luminance differently making precise contrast control difficult
Solution Approach 1:
The system changes the primary control parameter to relative luminance values, which directly determine contrast ratios. This parameter change provides precise control over luminance while maintaining adaptability, as users can still navigate the full color gamut by selecting from available colors and then adjusting their luminance values to achieve target contrasts.
Data Source
AI summary
Techniques are described for modification of color contrast ratio based on target contrast that overcome the challenges experienced in conventional systems for color contrast selection. In an implementation, a user leverages a content editing system to select a color set for contrast analysis. Utilizing the selected color set, the content editing system determines whether the color set exhibits a target contrast ratio. Further, the content editing system performs modification of the color set to generate candidate color sets that improve (e.g., increase) a contrast ratio of the original color set. The content editing system, for instance, manipulates color values (e.g., luminance values) of the original color set to increase a contrast ratio of the colors and generate different candidate color sets that are applicable to digital content.