Paint Coating Match Ratings for Color and Texture Selection
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Solution Overview
Problem
Existing methods struggle to provide consistent and understandable correlations between target coatings and proposed matches, particularly in terms of color and texture, due to the complexity and large datasets involved in coating information processing.
Innovation Solution
A computerized method and system that utilizes spectrophotometric data to correlate target coatings with proposed matches, displaying human-understandable qualitative values such as coarseness, sparkle, and intensity, using human-perceived texture differences and statistical correlations to simplify and standardize texture information display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex coating datasets with multiple measurements from different angles are used to provide accurate coating information, then measurement precision is improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The patent segments complex coating measurements into distinct visual attributes (color, texture, sparkle, coarseness, glint) that can be independently analyzed and displayed. This segmentation allows the system to process multiple measurements from different angles by breaking them down into manageable attribute categories, resolving the contradiction between comprehensive measurement and processing complexity
Solution Approach 2:
The patent introduces an intermediary processing layer that transforms raw spectrophotometric data into human-perceived visual attributes. This intermediary step acts as a mediator between the complex measurement instrument and the end user, converting technical measurements into understandable descriptors while preserving measurement precision
2Measurement precision
If large datasets with multiple measurements from different angles are collected, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent creates simplified copies of complex coating data in the form of visual attribute descriptors (color, texture, sparkle ratings) that represent the essential characteristics without requiring users to interpret raw measurement datasets. This copying approach maintains measurement precision while dramatically improving ease of operation
Solution Approach 2:
The patent changes the parameter representation from raw spectrophotometric values to human-perceived visual attributes. By transforming the data parameters into descriptive ratings that match human perception, the system maintains scientific accuracy while improving user accessibility
3Manufacturing precision
If detailed texture information from multiple geometries is provided, then manufacturing precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent extends the concept of visual attribute description from color to texture, using analogous descriptors (coarseness, sparkle, glint) for texture as color descriptors are used for color. This consistent approach to visual attribute description improves ease of operation while maintaining manufacturing precision for texture matching
Data Source
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AI summary
A computerized method for displaying matches of a paint sample to various proposed paint coatings includes receiving one or more coating texture variables of a target coating from a coating-measurement instrument. The method also includes displaying, on a digital display device, effect texture ratings for multiple respective proposed coating matches on a digital display device, wherein the effect texture ratings indicate a similarity between the one or more coating texture variables of the target coating and respective coating textures variables of each of the respective proposed coating matches. In addition, the method includes ordering the proposed coating matches, wherein the ordering indicates a strength in similarity between the target coating and each of the proposed coating matches with respect to the effect texture ratings.