Data Matrix Fixed-Pattern Inspection for Consistent Label Quality
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Solution Overview
Problem
Conventional barcode readers cannot selectively inspect specific elements of secondary battery labels, leading to inconsistent quality assessment due to variations in performance among different models, and there is a need for consistent criteria to ensure label quality.
Innovation Solution
A method and apparatus that utilize an imaging unit to capture an image of the label, extract a data matrix region, and inspect fixed pattern regions such as line and dot regions to determine label quality by analyzing pixel and dot counts, with the ability to adjust inspection regions to minimize over-inspection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional barcode readers are used to inspect label quality, then the inspection process is simple, but the measurement precision and consistency are poor due to variations in performance among different models
Solution Approach 1:
The patent segments the label into specific regions of interest (data matrix region, fixed pattern regions, line regions, dot regions) and inspects each region separately using image processing. This allows precise inspection of critical areas while ignoring non-critical areas, improving measurement precision without requiring complex universal inspection equipment.
Solution Approach 2:
The patent introduces an image processing system as an intermediary between the label and the inspection decision. The system captures an image of the label, processes it to extract specific regions, and applies consistent analysis algorithms to these regions. This intermediary layer eliminates the performance variations inherent in different barcode reader models.
2Reliability
If the entire label is inspected, then comprehensive quality assessment is achieved, but over-inspection occurs increasing false positives and reducing productivity
Solution Approach 1:
The patent applies local quality inspection by focusing only on specific regions of the label that are critical for quality assessment (data matrix region, fixed pattern regions, line regions, dot regions). By concentrating inspection resources on these local areas rather than the entire label, the system maintains high reliability while reducing over-inspection and improving productivity.
Solution Approach 2:
The patent uses partial action by inspecting only the necessary portions of the label (fixed pattern regions within the data matrix region) rather than the entire label. This partial inspection approach is sufficient to detect quality issues while avoiding the excessive action of inspecting non-critical areas, thereby reducing false positives and maintaining high throughput.
3Measurement precision
If fixed pattern regions are extracted and analyzed, then measurement precision is improved, but the processing time increases
Solution Approach 1:
The patent performs preliminary action by pre-defining the regions of interest (data matrix region, fixed pattern regions, line regions, dot regions) based on the label's structural characteristics. By identifying and extracting these specific regions before detailed analysis, the system improves measurement precision while minimizing processing time through targeted rather than exhaustive analysis.
Data Source
AI summary
A method is 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.