Digital Coating Database Using Spatial Micro-Color Analysis
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Solution Overview
Problem
Existing methods for matching the color and appearance of target coatings, such as those used in automotive repair, are cumbersome and expensive, particularly when dealing with variations in vehicle coatings due to different production sources and models, and require either costly spectrophotometers or cumbersome fandecks.
Innovation Solution
A sample database system that includes spatial micro-color analysis and machine learning to match target coatings by linking sample coating formulas with image features, utilizing electronic imaging devices to capture and analyze pixel differences and illumination effects, enabling accurate color and appearance matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spectrophotometers are used to measure color and appearance attributes, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses electronic imaging devices to capture digital images of coatings, creating a visual copy that can be analyzed computationally. This replaces the need for expensive spectrophotometers by using camera-based imaging systems that capture color and appearance data through photographs, which are then processed using image analysis algorithms to extract chromaticity and other coating attributes.
Solution Approach 2:
The patent replaces the mechanical/optical measurement system of spectrophotometers with an electronic imaging and computational analysis system. Instead of using complex optical instruments to directly measure color attributes, the system uses digital cameras to capture images and employs computer algorithms to analyze pixel data and determine coating characteristics, thereby simplifying the hardware while maintaining measurement capability.
2Adaptability or versatility
If fandecks with numerous sample coating layers are used, then adaptability is improved, but ease of operation deteriorates
Solution Approach 1:
The patent creates a digital database that stores image data and coating formula information, replacing the physical fandeck with an electronic system. Users can access and compare multiple coating samples through digital images displayed on screens, eliminating the need to physically handle and visually compare numerous printed or physical coating swatches, thereby improving ease of operation while maintaining comprehensive adaptability.
Solution Approach 2:
The patent transitions from a two-dimensional physical fandeck to a multi-dimensional digital database system. The database stores not only images but also associated metadata, coating formulas, and analytical data, allowing users to search, filter, and compare samples across multiple dimensions (color space, lighting conditions, viewing angles) without the physical constraints of a traditional fandeck layout.
3Ease of operation
If visual comparison with fandecks is used, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent replaces subjective visual comparison with objective computational image analysis. Digital images of both target coatings and database samples are analyzed using algorithms that quantitatively compare chromaticity values, pixel distributions, and color space coordinates. This automated analysis eliminates human visual variability and provides precise, repeatable measurements while maintaining user-friendly operation through software interfaces.
Solution Approach 2:
The system provides automated feedback by computationally comparing target coating images with database samples and ranking matches based on quantitative metrics. The image analysis software calculates chromaticity differences, pixel feature comparisons, and similarity scores, providing objective feedback to users about which coating formulas best match the target, thereby improving precision over subjective visual assessment.
4Adaptability or versatility
If comprehensive sample databases with multiple vehicle variations are included, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex task of color matching into distinct analytical components: image capture, pixel-level analysis, chromaticity calculation, and formula matching. The database stores data in structured segments (image files, metadata, coating formulas) that can be independently processed. This segmentation allows the system to handle diverse vehicle variations by applying the same modular analysis pipeline to each sample, managing complexity through systematic decomposition.
Solution Approach 2:
The patent manages database complexity by transforming raw image data into standardized parameter representations, such as chromaticity coordinates in specific color spaces (e.g., CIE L*a*b*). By converting diverse coating appearances into unified parameter sets, the system can efficiently store, search, and compare samples across different vehicles, lighting conditions, and viewing angles without proportionally increasing operational complexity. Users interact with standardized parameters rather than raw image data.
Data Source
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AI summary
Systems and methods for a sample database are provided, where the sample database is for matching a target coating. In one embodiment, the system comprises a sample database stored on a storage device. The sample database includes a sample coating formula and a sample image feature with at least one sample coating formula linked to at least one sample image feature. At least one sample image feature includes a spatial micro-color analysis that includes a value determined by a sample pixel feature difference between at least two sample pixels.