Ambient Color Sensor Array Clustering for Display Adaptation
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Solution Overview
Problem
Existing systems face challenges in accurately determining colorimetric values using multiple ambient color sensors due to the complexity of coordinating and processing multiple colorimetric measurements for effective ambient-adaptive display color rendering.
Innovation Solution
A system and method that utilize multiple ambient color sensors to collect and process color measurements, employing automated clustering techniques and transformation functions to generate a single accurate colorimetric value by selecting and weighting colorimetric values based on lighting clusters and perceptual color space coordinates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple ambient color sensors are used to improve color measurement accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent divides the color measurement task into segments by using multiple sensors positioned at different locations, each capturing colorimetric data from its local environment. The system then processes these segmented measurements separately before combining them, allowing parallel processing and reducing the complexity of coordinating a single comprehensive measurement.
Solution Approach 2:
The patent combines colorimetric values from multiple ambient color sensors using a weighted average or selection algorithm. By merging the measurements from multiple sensors according to their respective lighting cluster assignments and perceptual color space coordinates, the system achieves improved measurement precision while managing complexity through systematic combination rules.
2Adaptability or versatility
If multiple ambient color sensors are deployed to enhance adaptability to various lighting conditions, then adaptability is improved, but processing complexity increases
Solution Approach 1:
The patent performs preliminary classification of colorimetric values by assigning each sensor measurement to a lighting cluster based on its characteristics before final processing. This preliminary action organizes the data from multiple sensors into structured groups, enabling more efficient subsequent processing and reducing the overall processing complexity while maintaining high adaptability.
Solution Approach 2:
The patent transforms colorimetric values into perceptual color space coordinates and applies weighting factors based on lighting cluster characteristics. By changing the parameter representation and applying context-dependent weights, the system enhances adaptability to various lighting conditions while managing processing complexity through standardized transformation procedures.
3Measurement precision
If automated clustering techniques are applied to select and weight colorimetric values, then measurement precision is improved, but computational requirements increase
Solution Approach 1:
The patent implements automated clustering techniques that enable the system to self-organize and select the most appropriate colorimetric values from multiple sensors based on their inherent characteristics. The clustering algorithm automatically identifies patterns and assigns weights without requiring extensive manual intervention or complex computational models, improving measurement precision while moderating computational requirements.
Data Source
Figure 1A
Figure 1B~1D
Figure 1E~1G
AI summary
Systems and methods for determining a colorimetric value from color measurements for multiple ambient color sensors which for each color measurement, in various approaches, select a lighting cluster similar to the color measurement and determine whether the color measurement is valid or invalid based on a calculated similarity between the color measurement and the selected lighting cluster, calculate a weight for the color measurement for combination with other color measurements based on the calculated similarity between the color measurement and its selected lighting cluster, determine whether the color measurement is valid or invalid based on perceptual color space distances for the color measurement for multiple reference light sources, and/or calculate a weight for the color measurement for combination with other color measurements based on the perceptual color space distances for multiple reference light sources.