Academic Journal of Engineering and Technology Science, 2024, 7(6); doi: 10.25236/AJETS.2024.070601.
Ziyang Wang, Xingkun Li, Guodong Chen
School of Naval Architecture and Port Engineering, Shandong Jiaotong University, Weihai, Shandong Province, 264209, China
Efficient and accurate barcode recognition and localization play a crucial role in achieving automated and efficient management of medical printers. However, traditional barcode image localization algorithms are highly sensitive to environmental changes, and their accuracy often declines with variations in lighting conditions and shifts in the barcode's position. This paper proposes a deep learning-based recognition algorithm model, YOLO-BAR, which enhances the spatial semantic information extraction capability of the YOLOv8 backbone through the CBAM attention mechanism. Integrating YOLO-BAR into the CIS scanning process significantly improves the accuracy and efficiency of barcode recognition in medical printers.
Image recognition; Medical printers; Deep learning; YOLO-BAR
Ziyang Wang, Xingkun Li, Guodong Chen. Research on Printer Barcode Localization Method Based on Deep Learning. Academic Journal of Engineering and Technology Science (2024) Vol. 7, Issue 6: 1-6. https://doi.org/10.25236/AJETS.2024.070601.
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