Coating Detection System Using Color Coordinate Analysis
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Solution Overview
Problem
End consumers and industry specialists face difficulties in detecting and verifying the presence of thin film coatings on glass surfaces, such as low-E or antimicrobial coatings, due to their thinness and transparency, requiring expensive tools like spectrophotometers, which are not accessible to a broad audience.
Innovation Solution
An electronic coating detection and recognition system using a camera with processing resources to capture images or videos of coated articles, calculate color coordinate characterizations, and compare them to a database of known coatings, allowing for the identification and recognition of coatings without the need for specialized equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expensive specialized tools like spectrophotometers are used, then coating detection accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses a camera to capture optical reflections from coated surfaces, creating a digital copy of the optical properties. This digital representation is then analyzed to detect coatings, replacing the need for expensive physical spectrophotometers while maintaining detection capability through image processing and color coordinate analysis
Solution Approach 2:
The patent replaces complex mechanical/optical measurement systems (spectrophotometers) with a simpler camera-based optical system. By substituting sophisticated measurement mechanics with a common camera device and computational analysis, the system achieves coating detection without requiring specialized expensive equipment
2Reliability
If thin film coatings are made highly transparent, then functional performance is improved, but detectability worsens
Solution Approach 1:
The patent detects coatings by analyzing color coordinate characterizations (CIE L*a*b* or CIE x*y*) of light reflections from coated surfaces. Different coatings produce distinct color signatures in these coordinate systems, allowing detection of transparent thin films through subtle color variations that are imperceptible to the human eye but quantifiable through computational analysis
Solution Approach 2:
The patent transforms the detection problem from direct visual observation (2D surface view) to color coordinate space analysis (3D L*a*b* or x*y* coordinates). By mapping reflection colors into multidimensional color space and comparing against database signatures, the system detects transparent coatings through dimensional transformation rather than direct visual inspection
3Ease of operation
If simple visual inspection is used, then ease of operation is improved, but measurement precision worsens
Solution Approach 1:
The system uses a smartphone or portable device with built-in camera and processing capabilities to perform self-contained coating detection. The device captures images, processes color coordinates, compares against databases, and provides results autonomously without requiring specialized equipment or expert operators, enabling end consumers to verify coatings themselves
Solution Approach 2:
The patent pre-populates a database with color coordinate characterizations of known coatings before use. This preliminary preparation allows the system to quickly compare captured reflections against known signatures during operation, enabling accurate detection without requiring real-time complex analysis or expert knowledge
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables reliable and accessible detection and recognition of coatings on glass surfaces with high accuracy, using a smartphone or dedicated device, facilitating user-friendly identification of coating types and surfaces, even for end consumers without specialized tools.
Implementation Method 1
capture, using the camera, an image and/or video of an article onto which a source light is shown, the captured image and/or video including source light reflections associated with each major surface of the article
Implementation Method 2
calculate a color coordinate characterization for each of the identified source light reflections
Data Source
AI summary
Certain example embodiments relate to detecting and recognizing coatings on articles. A captured image and/or video of an article includes source light reflections associated with each major surface of that article. A color coordinate characterization for each source light reflection is calculated. Detection and recognition of any coatings formed on the major surfaces of the article is performable by comparing the calculated color coordinate characterizations and/or changes between calculated color coordinate characterizations to information stored in a data store including known color coordinate characterizations and/or known changes between color coordinate characterizations for different known coatings. Responsive to the detection and recognition of coating(s), there is generated output indicating the major surface(s) on which each detected and recognized coating is formed, an identifier of each detected and recognized coating, a likelihood associated with the detection and recognition of each detected and recognized coating, and an indication of any likely uncoated surfaces.