基于深度学习的医疗标签条形码检测与识别方法

Hui Zhang, Guoliang Shi, Li Liu, M. Zhao, Zhicong Liang
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引用次数: 10

摘要

条码技术的广泛应用导致了应用场景的复杂性。在传统的条码识别方法中,对于光照不均匀、失真、遮挡等问题没有通用的解决方案。本文采用深度学习理论来解决上述情况下的条码检测问题。并在此基础上解决了修正线性失真数据矩阵码的问题,突破了复杂情况下条码识别的关键技术。经过测试,识别速度达到125ms,识别准确率达到93%左右。该系统采用CCD摄像头采集图片,采用HALCON搭建处理算法,使用Visual Studio平台搭建软件,实现了药品包装上的日期矩阵码、药品电子监管码和产品条形码的快速准确识别。所开发的系统还可以检测条码和数据矩阵码的旋转角度,有利于读取条码信息。整个过程是实时的。
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Detection and identification method of medical label barcode based on deep learning
The widespread use of barcode technology has led to the complexity of the application scenario. In the traditional barcode recognition method, there is no universal solution to the problems of uneven illumination, distortion, and sheltered. In this paper, the deep learning theory is used to solve the problem of barcode detection under the above situation. And on this basis, the problem of correcting linear distortion Data Matrix code is solved, and the key technology of barcode recognition under complex situation is broken through. After testing, the recognition speed reached 125ms, and the recognition accuracy reached about 93%. The system uses CCD camera to collect pictures, adopts the HALCON to build the processing algorithm, and uses Visual Studio platform to build the software, which realizes the Date Matrix code, Drug Electronic Supervision Code and Product bar code fast and accurate identification on pharmaceutical packaging. The developed system can also detect the rotation angle of Barcode and Data Matrix code, which is favorable for reading the barcode information. The whole process is real-time.
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