Machine Vision Sheet Labeling with 2D Barcode Defect Encoding
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Solution Overview
Problem
Existing sheet defect inspection methods on production lines face inefficiencies due to unclear defect information, requiring experienced workers for accurate identification and analysis, which slows down the labeling process.
Innovation Solution
A machine vision-based sheet defect labeling method and apparatus that perform real-time defect inspection using a machine visual inspection device, generating a defect label with a two-dimensional barcode symbol including discontinuous dots, and labeling the defect at a preset position, thereby improving accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simple colors and shapes are used to distinguish different defects, then the labeling process is simple, but the defect information becomes unclear and requires experienced workers for identification
Solution Approach 1:
The patent transitions from traditional one-dimensional defect marking (colors and shapes) to two-dimensional barcode symbols. This dimensional change allows encoding of detailed defect information (type, location, size, quantity) within the compact 2D barcode structure, resolving the contradiction by providing both clear information representation and operational simplicity through automated scanning and recognition.
2Measurement precision
If experienced workers manually identify and analyze defects, then accurate defect identification is achieved, but the efficiency of sheet defect identification and analysis decreases
Solution Approach 1:
The patent replaces the mechanical human visual inspection and manual labeling system with an automated machine vision system. The machine vision device captures defect images, automatically identifies and analyzes defect characteristics, and generates 2D barcode labels with encoded defect information. This substitution maintains high accuracy through sophisticated image processing algorithms while dramatically improving productivity by eliminating manual intervention in the inspection and labeling process.
3Measurement precision
If detailed defect information is encoded in the defect label, then defect identification accuracy improves, but the complexity of the labeling system increases
Solution Approach 1:
The patent employs a universal 2D barcode symbol structure that can encode multiple types of defect information (type, location, size, quantity) within a single standardized format. This multi-functional encoding capability allows the labeling system to handle diverse defect information requirements without increasing structural complexity, as the same 2D barcode framework accommodates various information types through standardized data encoding schemes.
Data Source
AI summary
A machine vision-based sheet defect labeling method and apparatus, a device and a medium are provided. The method includes: performing a defect inspection on a target sheet conveyed to a preset defect inspection position, specifically, the target sheet continues to be conveyed towards a preset labeling position after passing the preset defect inspection position by being conveyed; generating a defect label of the target sheet when a defect present in the target sheet is determined, specifically, the defect label carries defect information represented by a two-dimensional barcode symbol including discontinuous dots; and labeling the defect of the target sheet at the preset labeling position with the defect label of the target sheet.