Chromatic Discriminability Verification Using Lab Color Space Thresholds
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Solution Overview
Problem
Current methods lack an accurate yet non-sensitive way to verify the chromatic discriminability of content, such as documents and images, across different color-vision characteristics groups, including normal color vision, color-blindness, and aging populations.
Innovation Solution
An information processing apparatus that converts designated verification points into Lab color space values, calculates color and lightness differences, and uses reference thresholds and correction factors to determine chromatic discriminability, considering whether regions are adjoining or apart, and adjusts thresholds based on color-vision characteristics and hue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing color verification methods are used, then verification can be performed, but the accuracy is insufficient and overly sensitive
Solution Approach 1:
The patent applies local quality by differentiating verification thresholds based on region adjacency. Adjoining regions use stricter thresholds (first reference threshold for color difference, third reference threshold for lightness difference) while non-adjoining regions use more lenient thresholds (second reference threshold for color difference, fourth reference threshold for lightness difference). This resolves the contradiction by making verification accuracy adaptive to spatial context rather than uniformly applied.
Solution Approach 2:
The patent changes verification parameters (thresholds) based on color-vision characteristics groups. Different threshold sets are applied for normal color vision, color-blindness (types P and D), and aging populations. This resolves the contradiction by adjusting verification sensitivity to match the specific visual capabilities of different user groups, achieving accurate yet non-overly-sensitive verification.
2Adaptability or versatility
If verification covers all color-vision characteristics groups, then comprehensiveness is improved, but complexity increases
Solution Approach 1:
The patent segments the verification process by dividing color-vision characteristics into distinct groups (normal color vision, color-blindness types P and D, aging populations). Each group has its own threshold parameters stored in the storage unit. This segmentation allows comprehensive coverage of different user groups while managing complexity through organized, modular parameter sets rather than a monolithic verification system.
Solution Approach 2:
The verification apparatus achieves universality by designing a single system that can verify chromatic discriminability for multiple color-vision characteristics groups. The storage unit contains multiple sets of reference thresholds that can be selected based on the target user group, making the same apparatus adaptable to diverse verification needs without requiring separate specialized systems for each group.
3Measurement precision
If region-specific thresholds are used, then verification accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing multiple sets of reference thresholds (first, second, third, fourth) and correction factors in the storage unit before verification is needed. The processor simply retrieves and applies the appropriate pre-prepared thresholds based on region adjacency and color-vision group, rather than calculating complex thresholds in real-time. This resolves the contradiction by shifting computational complexity from the verification process to the preliminary setup phase.
Data Source
AI summary
An information processing apparatus (10) for evaluating the chromatic discriminability of content includes: a unit (S12) that converts the color space values of each of first and second verification points A and B on the content into Lab color space values; a unit (S13) that calculates the color difference and the lightness difference between the first and second verification points based on the Lab color space values; and a unit (S23, S24) that determines color-difference discriminability by comparing the color difference between the first and second verification points with a color-difference threshold, and determines lightness-difference discriminability by comparing the lightness difference between the first and second verification points with a lightness-difference threshold. Each of the color-difference threshold and the lightness-difference threshold is set to a value that depends on whether a region containing the first verification point and a region containing the second verification point are adjoining or not.