Printing label defect detection method and device
By training the OCR optical character recognition model and comparing the electronic images and printed images of printed labels in real time, the problems of high cost and low efficiency of traditional manual detection are solved, and more efficient and accurate detection of printed label defects is achieved.
CN119693301AInactive Publication Date: 2025-03-25GUANGZHOU WEISHI TECHNOLOGY CO LTD
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Patent Information
- Application Number
- CN202411621902.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-14
- Publication Date
- 2025-03-25
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Technical Problem
Traditional printed label detection relies on labor, is costly, inefficient, prone to omissions, and has low detection accuracy.
Method used
By importing detection standard parameters, OCR optical character recognition model is trained, the print stream is intercepted in real time to generate electronic images, collect and import them into the OCR model for comparison, to identify defects in the printed label.
Benefits of technology
It improves detection accuracy and efficiency, reduces costs, reduces manual omissions, and achieves more efficient defect detection.
✦ Generated by Eureka AI based on patent content.
Abstract
The embodiment of the invention discloses a printing label defect detection method and device. The method comprises the following steps: importing detection standard parameters, and training an OCR (Optical Character Recognition) model; when it is detected that the label sends a printing instruction to the printer, a printing flow sent to the printer is intercepted in real time, and an electronic image is generated; collecting an actual printing image; importing the electronic image and the printing image into an OCR model for comparison so as to identify whether a printing label of the printing image has defects or not; detection precision and detection efficiency are improved, and cost is reduced.
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