Data Matrix Fixed-Pattern Inspection for Consistent Label Quality
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Solution Overview
Problem
Conventional label inspection methods for secondary batteries rely on barcode readers, which lack the ability to selectively inspect specific elements, leading to inconsistent quality assessment due to variations in reader performance.
Innovation Solution
A method and apparatus that utilize an imaging unit to extract fixed pattern regions from a data matrix on the label, applying binary processing and inversion to enhance contrast, and determine label quality based on preset thresholds, reducing over-inspection by selectively inspecting these regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If barcode readers are used for label inspection, then the inspection process is simple, but the measurement precision and consistency are poor due to variations in reader performance and inability to selectively inspect specific elements
Solution Approach 1:
The patent segments the label into specific regions of interest (fixed pattern regions within the data matrix) and inspects only those segments using image processing. This selective segmentation allows precise measurement of specific elements while maintaining a relatively simple overall inspection system, resolving the contradiction between simplicity and precision.
Solution Approach 2:
The patent replaces the mechanical barcode reader system with an optical imaging system combined with digital image processing. This substitution enables consistent, selective inspection of specific label regions through software-based analysis rather than relying on varying hardware performance, thereby improving measurement precision while keeping the system manageable.
2Reliability
If all regions of the label are inspected, then comprehensive quality assessment is achieved, but the productivity decreases due to over-inspection of non-critical areas
Solution Approach 1:
The patent applies local quality inspection by focusing computational resources and analysis only on specific fixed pattern regions within the data matrix that are critical for quality assessment. Non-critical areas are excluded from detailed inspection, thereby maintaining reliability for essential quality attributes while significantly improving productivity through reduced processing scope.
Solution Approach 2:
The patent extracts and isolates specific fixed pattern regions from the entire label for inspection. By taking out only the relevant portions (fixed patterns within data matrix) rather than inspecting the whole label, the system achieves comprehensive assessment of critical quality elements while enhancing productivity through selective processing.
3Measurement precision
If fixed pattern regions are extracted and used for inspection, then the measurement precision and consistency are improved, but the device complexity increases due to additional image processing steps
Solution Approach 1:
The patent creates a digital copy (image) of the label and performs all complex processing operations on this copy rather than manipulating the physical label. This copying approach enables sophisticated image processing (extraction, binarization, pattern recognition) to be performed on digital data, improving measurement precision while containing device complexity by keeping the physical inspection setup simple.
Solution Approach 2:
The patent transforms the inspection problem by changing parameters through image processing operations (binarization, contrast enhancement, region extraction). These parameter changes convert the raw image data into a form that is more suitable for precise measurement and analysis, improving consistency while managing complexity through algorithmic transformations rather than hardware complexity.
Data Source
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AI summary
A method and a vision inspection apparatus are provided for inspecting the quality of a label. The method includes receiving an image including the label by an imaging unit, extracting a data matrix region of the label from the image by an inspection unit, extracting at least one fixed pattern region from the data matrix region by the inspection unit, and determining an abnormality in quality of the label based on the extracted fixed pattern regions by the inspection unit.