Vehicle Illumination Luminance Analysis for Defective Pixel Visibility
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Solution Overview
Problem
Defective pixels in high-resolution lighting modules for vehicles can be invisible to human observers, posing a safety risk and affecting product quality, as the visibility of these defects is unpredictable based on light density differences.
Innovation Solution
A method that records and modifies digital images of luminance distribution from vehicle lighting devices using an algorithm simulating human visual processing, including optical and neural contrast sensitivity functions, to determine which elements are perceivable by humans, allowing for the prediction of pixel error visibility and decision-making on module replacement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution modules are used in lighting devices, then the light image quality and detail resolution are improved, but the risk of defective pixels causing visible distractions increases
Solution Approach 1:
The patent applies preliminary action by performing visibility prediction analysis before the lighting device is deployed. The method records the luminance distribution, simulates human visual processing, and identifies potentially visible defective pixels in advance, allowing for preventive replacement or adjustment before the device enters service, thus eliminating safety risks while maintaining high resolution
2Ease of manufacture
If absolute difference in light densities is used to detect defective pixels, then the detection process is simple, but the accuracy of predicting visibility is insufficient
Solution Approach 1:
The patent transforms the detection approach by changing parameters from simple absolute light density differences to a comprehensive visibility prediction model. This model incorporates multiple parameters including luminance distribution, spatial frequency, contrast sensitivity function, and visibility threshold, thereby achieving accurate visibility prediction while maintaining practical applicability
3Reliability
If all elements of luminance distribution are analyzed, then complete detection of pixel errors is achieved, but the complexity of analysis increases significantly
Solution Approach 1:
The patent applies the extraction principle by isolating and analyzing only those elements of the luminance distribution that are relevant to human visibility. The simulation process extracts perceptually significant information while filtering out irrelevant data, and the visibility threshold further extracts only the defective pixels that would actually be visible to humans, thereby reducing analysis complexity while maintaining detection completeness
Data Source
AI summary
A method for analyzing the luminance distribution of light emanating from an illumination device for a vehicle. A digital image that corresponds to a luminance distribution of light emanating from an illumination device of a vehicle is recorded. The digital image is modified such that the modified image is a reconstruction of the luminance distribution, the reconstruction containing at least substantially still only the elements or parts of the luminance distribution that are perceptible to humans.