Material Appearance Visualization for Gonioapparent Color Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing color matching methods struggle to accurately match the appearance, including angle-dependent color and texture, of materials with gonioapparent properties, such as metallic flakes or interference flakes, especially when producing paint coatings for vehicle repairs where the body shop lacks color mixing facilities.
Innovation Solution
A method and system for visualizing the appearances of materials by combining measured and calculated texture attributes using a geometric model, allowing realistic visualization of materials under various illumination and viewing directions, and adjusting pixel values to match statistical properties, even when texture information is limited.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual color matching methods are used, then color professionals can obtain acceptable matches through iterative trial and error, but the process is time-consuming and requires multiple physical trial objects to be produced
Solution Approach 1:
The system performs preliminary visualization of the candidate material appearance using measured texture attributes from reference materials and calculated texture attributes from the geometric model and recipe, allowing color professionals to assess the match quality before producing physical trial objects. This preliminary visual assessment reduces the need for iterative physical trials.
Solution Approach 2:
The system creates a visual copy or representation of the candidate material appearance through rendering the geometric model with the calculated texture attributes and measured appearance attributes. This digital copy allows assessment of the color match without requiring physical trial objects, saving time and materials.
2Productivity
If color formulation software is used to predict candidate recipes, then fewer iterations are needed compared to manual methods, but the software cannot accurately predict the appearance of materials with gonioapparent properties under different illumination and viewing directions
Solution Approach 1:
The system incorporates angle-dependent texture attributes by using a geometric model that accounts for different illumination and viewing directions. The measured appearance attributes include angle-dependent properties, and the rendering process visualizes how the material appearance changes with viewing angle, providing a more comprehensive assessment for gonioapparent materials.
Solution Approach 2:
The system changes the parameters used to describe material appearance by including not just color values but also texture attributes such as roughness, anisotropy, and angle-dependent reflectivity. These additional parameters enable accurate prediction and visualization of gonioapparent material properties under different lighting and viewing conditions.
3Measurement precision
If measured appearance attributes are used for visualization, then accurate representation of target material is achieved, but texture information may be incomplete or insufficient for full appearance reconstruction
Solution Approach 1:
The system merges measured appearance attributes from the target object with calculated texture attributes derived from the geometric model and material recipe. By combining these two sources of information, the system compensates for incomplete measured texture data and achieves a more complete and accurate representation of the material appearance.
Solution Approach 2:
The geometric model acts as an intermediary that bridges the gap between incomplete measured texture information and the full appearance representation. The model uses the material recipe and optical properties to calculate missing texture attributes, effectively mediating between limited measurements and complete appearance reconstruction.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
First and second sets of appearance attributes are obtained. The first set is associated with a target material. It comprises measured appearance attributes (54) of the target material. The second set is associated with a candidate material. It comprises candidate appearance attributes that are based on appearance attributes associated with one or more reference materials. A geometric model of at least one virtual object (72) is obtained, the geometric model defining a three-dimensional surface geometry. A scene comprising the at least one virtual object (72) is visualized. First and second portions of the virtual object (72) are visualized using the first and second sets of appearance attributes, respectively. Each of the first and second sets of appearance attributes comprises texture attributes in the form of a plurality of sets of image data. The image data in one of the sets may be based on texture attributes of the other set., or the image data in the second set may be synthesized from image data associated with a plurality of constituent materials of the candidate material.