Color Classification Matrix Using Chroma and Greying Scales
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Solution Overview
Problem
Existing color classification systems, such as the Munsell and CIELAB systems, fail to adequately account for the unique characteristics of colors like culture, style, and type, leading to difficulties in identifying, understanding, designating, and harmonizing colors effectively.
Innovation Solution
A scientifically founded color classification system that uses a matrix based on the perception of colors by the human brain, specifically considering the degree of saturation of chroma and greying, allowing for the classification of colors into clusters and families, and providing a unique identification code for each color to facilitate navigation and harmonization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the Munsell color system is used for color classification, then colors can be designated and classified based on hue, lightness and chroma, but the system lacks a well-founded scientific basis and does not meet current needs for color representation and reproducibility
Solution Approach 1:
The patent transforms the color classification approach by changing the fundamental parameters from Munsell's intuitive hue-lightness-chroma to a scientifically-based system using CIELAB coordinates (L*, a*, b*) combined with chroma and hue angle calculations. This parameter transformation provides both scientific rigor and improved measurement precision for color classification
Solution Approach 2:
The patent replaces the manual, experimental Munsell system with an automated computational approach using colorimetric formulas and mathematical calculations. The system substitutes human visual assessment with objective mathematical transformations from device color spaces (RGB, CMYK, HEX) to the classification framework, eliminating subjectivity and improving reproducibility
2Ease of operation
If traditional color classification systems are used, then colors can be organized in three-dimensional models, but they do not sufficiently allow users to identify, understand, designate, use, harmonize and communicate colors
Solution Approach 1:
The patent segments the continuous color space into discrete, meaningful categories by calculating chroma (C* = sqrt(a*² + b*²)) and hue angle (h° = atan2(b*, a*)) from CIELAB coordinates. This segmentation creates identifiable color families and relationships, making it easier for users to understand and communicate colors while preserving essential color characteristics
Solution Approach 2:
The patent introduces an intermediary computational layer that transforms raw color data into meaningful classification attributes. The system acts as a mediator between device color spaces and human color perception, providing structured information about color relationships, harmonies, and characteristics that facilitates both identification and communication
3Quantity of substance
If all visible colors are classified, then complete color coverage is achieved, but colors with insufficient saturation or excessive greying are included that are not perceived strongly by color receptors
Solution Approach 1:
The patent uses chroma (C*) as a filtering parameter to distinguish perceptually significant colors from those with insufficient saturation. By setting minimum chroma thresholds, the system automatically excludes colors that would not be strongly perceived by human color receptors, maintaining quantity of meaningful colors while eliminating perceptually degraded entries
Data Source
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AI summary
The present invention relates to a method for classifying colors and grey shades, including the classification of colors in a matrix, in which the colors In the matrix belong to a same subfamily and in which the position of a color in the matrix is determined by the degree of color degree of saturation of chroma and the degree of greying of the color, characterised in that the scale for the degree of color degree of saturation of chroma as well as the scale for the degree of greying are linear, in which the scale for the degree of greying depends on the scale for the degree of color degree of saturation of chroma and in which the greying steps are dynamic in function of the color degree of saturation of chroma.