Color Fidelity Testing Using Pre-Computed Transformation Matrices
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Solution Overview
Problem
Current methods for determining color fidelity and human-perceptible color differences between two colors specified by color vectors are resource-intensive and complex, particularly when converting color values from image sensors to the CIELAB color space for frequent comparisons in automated object inspection.
Innovation Solution
A method that determines color fidelity by calculating the color distance in the RGB color space and using a multiplier to approximate the color difference in the CIELAB space, with a quantization space to simplify calibration and reduce memory requirements, allowing for efficient determination of color differences using a device with a color brightness sensor, distance formation unit, quantization unit, and multiplier memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If color values are transformed into CIELAB color space for accurate human-perceptible color difference calculation, then measurement precision is improved, but device complexity and computational resource load increase
Solution Approach 1:
The patent pre-calculates and stores transformation matrices that map from device-specific color spaces (e.g., sRGB, Adobe RGB) directly to CIELAB color space. These pre-computed matrices are stored in lookup tables, allowing rapid color difference calculation without performing complex real-time transformations. This preliminary preparation eliminates the need for iterative optimization during actual color measurement operations.
Solution Approach 2:
The patent creates simplified mathematical models (copy representations) of the complex CIELAB transformation process. Instead of performing the full nonlinear transformation with its many computational steps, the system uses pre-derived linear approximation matrices that replicate the essential behavior of the transformation. This copying approach maintains measurement precision while dramatically reducing computational complexity.
2Measurement precision
If full CIELAB transformation is performed for each color comparison, then measurement precision is improved, but productivity decreases due to high computational resource load
Solution Approach 1:
The system performs the computationally intensive CIELAB transformation matrices preparation in advance, storing the results in optimized data structures. During actual color comparison operations, the system simply applies these pre-computed matrices through straightforward matrix multiplication operations, achieving both high precision and fast processing speeds.
Solution Approach 2:
The patent divides the color space transformation process into separate, independent matrix operations for each color channel and transformation step. This segmentation allows the computational workload to be distributed and parallelized, improving processing throughput while maintaining the accuracy of the complete transformation chain.
3Measurement precision
If accurate color transformation is performed for every measured value, then measurement precision is improved, but loss of time increases due to repeated complex calculations
Solution Approach 1:
The patent pre-computes the transformation matrices and stores them in readily accessible memory. When color measurements are taken, the system retrieves these pre-computed matrices and applies them immediately without repeating the complex transformation derivations. This eliminates redundant calculations and significantly reduces the time required for each color comparison operation.
Data Source
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AI summary
The method involves determining the color difference (delta R) between the two color vectors (E1,E2). A basic color vector is determined by one of the two color vectors or by combining the two color vectors in color space (R). A multiplier (delta E) is determined by selecting from multiple multipliers based on the basic color vector. The perceptible color difference or the color fidelity is determined as a color difference product and the multiplier product. An independent claim is included for a device for determining the color fidelity and for determining the human perceptible color difference between two colors provided by color vectors.