Display Cutting Line Detection Using Grayscale Difference Enhancement
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Solution Overview
Problem
Conventional methods for detecting the cutting line of a display apparatus suffer from significant detection errors due to small differences in grayscale values of pixels at the boundary, leading to inaccurate identification of the cutting line.
Innovation Solution
A method involving the recognition of a reference mark, generation of a measurement area, creation of a reference line, and determination of cutting points through increased grayscale value differences within designated detection areas, allowing for precise detection of the cutting line.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional grayscale value comparison method is used for cutting line detection, then the detection process is simple, but the detection accuracy is low due to small grayscale value differences at boundaries
Solution Approach 1:
The patent applies preliminary action by performing grayscale value enhancement and difference calculation on pixel data before actual cutting line detection. The system pre-processes the image data by calculating grayscale differences between adjacent pixels and enhancing these differences, so that when cutting line detection is performed, the already-enhanced data provides higher accuracy without requiring complex detection algorithms.
Solution Approach 2:
The patent changes parameters by transforming the original grayscale values into enhanced grayscale difference values. Instead of directly comparing raw grayscale values at the cutting line, the system calculates and enhances the difference between adjacent pixel grayscale values, thereby changing the parameter from absolute grayscale to grayscale differential, which significantly improves detection accuracy.
2Measurement precision
If the measurement area is positioned close to the reference mark for efficient detection, then the detection speed is improved, but the grayscale value difference becomes even smaller making detection more error-prone
Solution Approach 1:
The patent applies local quality by differentiating the treatment of different measurement areas. Instead of uniformly processing the entire measurement area, the system selectively enhances grayscale differences in specific local regions where cutting lines are expected to occur. This allows the system to focus computational resources on critical areas, improving accuracy without proportionally increasing processing time across the entire image.
Solution Approach 2:
The patent uses partial action by applying grayscale enhancement only to specific detection-relevant areas rather than processing the entire image uniformly. The system identifies and enhances only the portions of the measurement area where cutting lines are likely to be detected, thereby achieving high detection accuracy while minimizing unnecessary processing time on irrelevant regions.
3Reliability
If multiple detection areas are generated within the measurement area to improve accuracy, then the detection reliability is improved, but the processing complexity and time increase
Solution Approach 1:
The patent applies segmentation by dividing the measurement area into multiple detection areas, each targeting specific regions where cutting lines are expected. By segmenting the measurement area into smaller, focused detection zones, the system can independently analyze each segment with enhanced grayscale differences, thereby improving overall detection reliability while keeping the processing load manageable through localized analysis.
Solution Approach 2:
The patent uses partial action by generating and processing only the necessary detection areas within the measurement area rather than analyzing the entire image. The system strategically positions detection areas only where cutting lines are expected to occur, based on pre-processing information, thereby improving reliability through multiple targeted detection points while avoiding the productivity loss that would result from processing the complete image area.
Data Source
AI summary
A method of detecting a cutting line of a display apparatus includes recognizing a reference mark from a captured image of the display apparatus including a first area extending along a boundary of a substrate, a second area positioned on an inner side of the first area, and a background area positioned on an outer side of the first area, designating a measurement area in the captured image to be apart from the reference mark by a preset distance toward the boundary of the substrate, generating a reference line parallel to the boundary of the substrate, within the measurement area, generating detection areas within the measurement area, increasing a difference between grayscale values of pixels constituting the measurement area, determining cutting points in each of the detection areas and detecting the cutting line based on the cutting points, and measuring a distance between the cutting line and the reference mark.