Diagonal Mura Detection via Luminance and Shape Feature Analysis
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Solution Overview
Problem
Existing display defect detection methods struggle to accurately detect diagonal Mura in display panels due to limitations in capturing fine defects and subjective human error, leading to inconsistent detection results.
Innovation Solution
A display defect detection system comprising a preprocessing circuit and a Mura detection circuit that processes a capture image of a test pattern displayed by a display panel to enhance image quality and calculate a final feature value for diagonal Mura detection, improving accuracy by considering luminance differences and shape ratios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a worker directly detects Mura with eyes, then detection is simple and fast, but detection accuracy is low and inconsistent due to fatigue and subjective determination
Solution Approach 1:
The patent replaces the mechanical human visual system with an automated image processing system that captures display panel images and processes them through algorithms to detect Mura defects. This substitution eliminates human fatigue and subjectivity while maintaining detection capability through computational methods.
Solution Approach 2:
The patent introduces an image processing system as an intermediary between the display panel and the detection outcome. This intermediary captures images, processes them through multiple algorithms (including edge detection and luminance analysis), and produces objective detection results without direct human involvement in the measurement process.
2Measurement precision
If conventional Mura detection algorithms are used, then detection automation is achieved, but detection accuracy is low because boundary, brightness change, and contrast are not clearly shown
Solution Approach 1:
The patent segments the Mura detection process into multiple distinct algorithmic components: edge detection to identify boundaries, luminance analysis to detect brightness changes, and contrast calculation to measure intensity differences. Each segment addresses a specific aspect of Mura detection that was previously handled inadequately by conventional single-algorithm approaches.
Solution Approach 2:
The patent extends detection from traditional 2D image analysis by incorporating multiple processing dimensions including edge maps, luminance profiles, and contrast measurements. This multi-dimensional approach allows the system to detect Mura defects that are not apparent in standard brightness-only analysis, thereby improving detection accuracy for subtle defects.
3Measurement precision
If conventional algorithms based on contrast ratio and standard deviation are used, then simple processing is achieved, but accuracy of diagonal Mura detection is limited due to various line directions and lengths
Solution Approach 1:
The patent implements dynamic algorithm selection and parameter adjustment based on the detected characteristics of Mura defects. The system adapts its processing approach according to the orientation, length, and position of detected lines, allowing it to effectively handle diagonal Mura with various line directions and lengths that static conventional algorithms cannot detect accurately.
Data Source
AI summary
A display defect detection system and a detection method thereof are disclosed. A display defect detection system includes a preprocessing circuit receiving a capture image of a test pattern, displayed by a display panel, as a panel image including diagonal Mura and preprocessing the panel image to output a preprocessing image and a Mura detection circuit calculating a final feature value of the diagonal Mura by multiplying a first feature value, in which a luminance difference of the diagonal Mura is reflected, by a second feature value in which a shape ratio of the diagonal Mura is reflected, on the basis of an edge map of the preprocessing image, and detecting a display position of the diagonal Mura on the basis of the final feature value of the diagonal Mura.