Dark State Image Uniformity Detection Using CIE-LCH Statistical Analysis
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Solution Overview
Problem
Manual detection of uniformity in dark state images of flat-panel displays is inefficient and prone to missed detections due to the reliance on human eye comparison, lacking a unified standard.
Innovation Solution
A method and device for image detection that divides the dark state image into areas, calculates RGB values, converts them to XYZ and L* C* values, performs statistical analysis, and determines a dark state uniformity coefficient using specific formulas to establish a standard for evaluating uniformity, facilitating unified detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual detection by human eye is used to evaluate uniformity of dark state image, then the detection process is simple and easy to operate, but the detection precision is low and missed detections occur frequently
Solution Approach 1:
The patent replaces the manual human-eye detection mechanism with an automated image processing system. The system captures dark state images using an imaging device, converts RGB values to CIE-LCH color space, and automatically calculates uniformity coefficients through statistical analysis. This substitution eliminates human subjectivity and fatigue-related errors while maintaining operational simplicity through automated workflow.
Solution Approach 2:
The patent transforms the detection parameters from direct human visual assessment to quantitative color space conversions and statistical metrics. By converting RGB values to CIE-LCH space and calculating L* uniformity coefficients, the system establishes objective numerical criteria for uniformity evaluation, replacing subjective human judgment with measurable parameters.
2Measurement precision
If automated image processing with color space conversion and statistical analysis is implemented, then the measurement precision and uniformity evaluation accuracy are improved, but the device complexity increases
Solution Approach 1:
The patent employs a multi-functional integrated system that performs image capture, color space conversion, statistical analysis, and uniformity evaluation within a single detection device. The imaging device captures dark state images, the processing unit executes comprehensive color space transformations (RGB to CIE-LCH), and the same system calculates multiple statistical parameters including mean, standard deviation, and uniformity coefficients, eliminating the need for separate specialized equipment.
Solution Approach 2:
The detection system is designed to be self-sufficient by integrating all necessary processing functions within the detection device itself. The system automatically captures images, performs color space conversions, executes statistical analyses, and generates uniformity evaluation results without requiring external complex equipment or manual intervention at each processing stage.
3Reliability
If comprehensive statistical analysis including multiple parameters (mean, standard deviation, Sobel value) is performed, then the reliability of uniformity evaluation is improved, but the processing time and productivity are reduced
Solution Approach 1:
The patent performs preliminary color space conversion from RGB to CIE-LCH before statistical analysis. By pre-converting the color data to the appropriate color space, the system prepares the data in advance for uniformity calculations, enabling more efficient processing during the statistical analysis phase. This preliminary action organizes the data structure to facilitate subsequent rapid computation of multiple parameters.
Solution Approach 2:
The detection system executes continuous automated processing through the complete workflow: image capture, color space conversion, statistical parameter calculation, and uniformity evaluation. The system maintains continuous operation without manual intervention between steps, processing multiple images and parameters in an unbroken sequence, which maximizes productivity while maintaining comprehensive analysis.
Data Source
AI summary
A method and device for detecting uniformity of a dark state image of a display is disclosed. After an acquired dark state image of a display panel is divided into a plurality of areas according to a preset rule, RGB values of each area are determined and converted into XYZ values. The L* and C* values in the CIE-LCH standard are calculated and statistical analysis is performed to the L* and C* values of the areas in the dark state image to determine statistical parameters of the display image. A dark state uniformity coefficient of the dark state image is determined based on the determined statistical parameters, and the uniformity of the dark state image of the display panel is determined through the dark state uniformity coefficient.