Display Panel Defect Detection via Image Sub-Image Mapping
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Solution Overview
Problem
Conventional methods for detecting defects in display panels during manufacturing fail to accurately locate and quantify defects due to difficulties in distinguishing between defect and normal areas.
Innovation Solution
An automatic detection method involving the acquisition of tag and mapped images, division into sub-images, determination of corner points, luminance histogram analysis, and correction using coordinate deviation values to accurately identify normal and defective areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image analysis method is used to detect defects, then the inspection process can be performed, but the defect location and difference between defect area and normal area cannot be accurately determined
Solution Approach 1:
The patent divides the original image into multiple sub-images through coordinate transformation and mapping. Each sub-image corresponds to a specific region of the display panel, enabling localized defect analysis. This segmentation allows precise determination of defect locations by analyzing each region separately and mapping results back to the original coordinate system.
Solution Approach 2:
The patent introduces a mapping relationship as an intermediary between the original image and the analyzed sub-images. By establishing coordinate transformation rules and mapping tables, the system can accurately translate defect positions from sub-image coordinates back to original image coordinates, preserving location precision throughout the analysis process.
2Measurement precision
If conventional image analysis is used, then defect inspection can be performed, but the defects cannot be quantified and discriminated
Solution Approach 1:
The patent performs preliminary coordinate transformation and image mapping before defect analysis. By pre-establishing the mapping relationship between original images and sub-images, and pre-calibrating coordinate systems, the system simplifies subsequent defect quantification tasks. This preliminary preparation enables direct comparison of defect areas across different regions without complex real-time calculations.
Solution Approach 2:
The patent transforms the image analysis problem by changing coordinate parameters and mapping relationships. Through coordinate transformation, scaling, and mapping table generation, the system converts complex defect measurement problems into simpler comparative analyses of mapped sub-images, enabling accurate quantification while managing computational complexity.
3Measurement precision
If high precision defect detection is implemented, then accurate defect location can be achieved, but the processing complexity increases
Solution Approach 1:
The patent segments the complex defect detection task into manageable steps: coordinate transformation, image mapping, sub-image analysis, and result synthesis. By dividing the overall process into distinct processing stages, each with specific functions, the system achieves high precision while keeping individual processing modules relatively simple and well-defined.
Data Source
AI summary
An automatic detection method for defects of a display panel is disclosed, which comprises: acquiring a tag image, a mapped original image and a mapped tag image; dividing the mapped original image into a plurality of mapped original sub-images, and dividing the mapped tag image into a plurality of mapped tag sub-images; acquiring a normal area and a defective area of the mapped original sub-images; merging the mapped original sub-images to discriminate the normal area and the defective area of the mapped original sub-images; correcting the discriminated normal area and the discriminated defective area of the mapped original sub-images by using the mapped tag image and the tag image to acquire a defect location of the display panel. The automatic detection method for defects of the display panel can accurately acquire the location of the defect and the difference between the defective area and the normal area to quantify and discriminate the defects of the display panel.